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Users stop relying on the platform and go back to spreadsheets or old tools.",[],{"_key":538,"_type":99,"children":539,"markDefs":544,"style":107},"42fecffcb2df",[540],{"_key":541,"_type":103,"marks":542,"text":543},"0286075085bc",[],"To keep both cost and performance under control, it helps to build guardrails into your Databricks implementation from day one:",[],{"_key":546,"_type":99,"children":547,"level":230,"listItem":231,"markDefs":552,"style":107},"830d49dc44e6",[548],{"_key":549,"_type":103,"marks":550,"text":551},"c94100068985",[],"Cost limits and naming rules so you can see who is spending what",[],{"_key":554,"_type":99,"children":555,"level":230,"listItem":231,"markDefs":560,"style":107},"2067207d774c",[556],{"_key":557,"_type":103,"marks":558,"text":559},"5c864dbe03e0",[],"Auto-termination policies so idle clusters shut down",[],{"_key":562,"_type":99,"children":563,"level":230,"listItem":231,"markDefs":568,"style":107},"15da0ae7930d",[564],{"_key":565,"_type":103,"marks":566,"text":567},"d2d1a7b9de6b",[],"Right-sizing guidance so teams know which cluster types to choose",[],{"_key":570,"_type":99,"children":571,"level":230,"listItem":231,"markDefs":576,"style":107},"dec67a442858",[572],{"_key":573,"_type":103,"marks":574,"text":575},"817ac4adcc07",[],"Performance baselines and monitoring, tied into your FinOps practices",[],{"_key":578,"_type":99,"children":579,"markDefs":584,"style":107},"b90c491c3ee4",[580],{"_key":581,"_type":103,"marks":582,"text":583},"7a8366ee2a70",[],"When these ideas are baked into the design, not added later, the environment stays healthy as adoption grows.",[],{"_key":586,"_type":99,"children":587,"markDefs":592,"style":182},"016922934b41",[588],{"_key":589,"_type":103,"marks":590,"text":591},"86d41a1a3236",[],"Talent Gaps, Skills Debt, and Change Fatigue",[],{"_key":594,"_type":99,"children":595,"markDefs":600,"style":107},"b541c13e5376",[596],{"_key":597,"_type":103,"marks":598,"text":599},"b23d0713f1f0",[],"Even the best-designed Databricks setup fails if people are not ready to use it. 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We bring structured readiness assessments, Databricks lakehouse reference architectures, and guided implementations that reduce risk for migration, modernisation, and day-to-day use of data and AI. 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AI Agents From Risk to Revenue",[],{"_key":878,"_type":99,"children":879,"markDefs":884,"style":107},"53ae9de9e8d9",[880],{"_key":881,"_type":103,"marks":882,"text":883},"501c65985431",[],"Enterprise AI agents are moving from small tests to sitting beside teams as real digital colleagues. They write first drafts, pull numbers, answer questions, and trigger actions in core systems. For many organisations, this is no longer a distant idea; it is becoming day-to-day work.",[],{"_key":886,"_type":99,"children":887,"markDefs":892,"style":107},"4d24e93172e6",[888],{"_key":889,"_type":103,"marks":890,"text":891},"5c34397bfca1",[],"There is a catch. If those agents sit on messy, poorly governed data, they can say the wrong thing to the wrong person at the worst time. They can leak sensitive data, act on old facts, or make choices that no one can explain later. This is where data governance stops being a paperwork exercise and becomes the safety net that keeps AI useful, safe, and trusted.",[],{"_key":894,"_type":99,"children":895,"markDefs":900,"style":107},"dd3e55d0b371",[896],{"_key":897,"_type":103,"marks":898,"text":899},"6a4283757bb5",[],"At Cosmos Thrace, we see the real advantage not in building the flashiest enterprise AI agents, but in building them on a well-governed lakehouse foundation. On platforms like Databricks, where Delta Lake, Unity Catalog, lineage, and access controls are built in, agents can move from risky experiments to trusted parts of daily work. In this article, we will share a practical blueprint for designing, governing, and running enterprise AI agents that are compliant, auditable, and ready for serious use across the new financial year.",[],{"_key":902,"_type":99,"children":903,"markDefs":908,"style":182},"66d96c79577d",[904],{"_key":905,"_type":103,"marks":906,"text":907},"7ea3bed27d30",[],"Why Data Governance Makes or Breaks Enterprise AI Agents",[],{"_key":910,"_type":99,"children":911,"markDefs":916,"style":107},"b430fc9719b0",[912],{"_key":913,"_type":103,"marks":914,"text":915},"3c713c8f02f2",[],"When people hear \"governance\", they often think of long policy documents that no one reads. For enterprise AI agents, governance is something different. It is live control over what data an agent can see, how fresh that data is, where it came from, and what the agent is allowed to do with it.",[],{"_key":918,"_type":99,"children":919,"markDefs":924,"style":107},"cd92f0efa4ad",[920],{"_key":921,"_type":103,"marks":922,"text":923},"5d6cd297ee10",[],"Without this, common failure modes appear very quickly:",[],{"_key":926,"_type":99,"children":927,"level":230,"listItem":231,"markDefs":932,"style":107},"6d3feb80983a",[928],{"_key":929,"_type":103,"marks":930,"text":931},"cc18877b4313",[],"Agents answer from stale data that was never approved",[],{"_key":934,"_type":99,"children":935,"level":230,"listItem":231,"markDefs":940,"style":107},"de9dab0c4d7f",[936],{"_key":937,"_type":103,"marks":938,"text":939},"54b00eb25316",[],"Role-based access is skipped because someone used a shared API key",[],{"_key":942,"_type":99,"children":943,"level":230,"listItem":231,"markDefs":948,"style":107},"8a11b02143db",[944],{"_key":945,"_type":103,"marks":946,"text":947},"518fb47dc7fc",[],"Confidential and public data are mixed inside the same prompt context",[],{"_key":950,"_type":99,"children":951,"level":230,"listItem":231,"markDefs":956,"style":107},"7fbf10b5d617",[952],{"_key":953,"_type":103,"marks":954,"text":955},"a8a04a6f734b",[],"Decisions are logged in chat windows, not in traceable, auditable systems",[],{"_key":958,"_type":99,"children":959,"markDefs":964,"style":107},"03ccc266e339",[960],{"_key":961,"_type":103,"marks":962,"text":963},"d10925fc50c0",[],"For finance, risk, and operations teams, trust is everything. They will only rely on an agent if every answer can be traced back to clearly governed sources, with clean lineage and clear logs. When a regulator, auditor, or internal review asks \"Where did this number come from?\" there must be a simple, confident answer.",[],{"_key":966,"_type":99,"children":967,"markDefs":972,"style":107},"d6a4ceddad2d",[968],{"_key":969,"_type":103,"marks":970,"text":971},"73ce3bbf3173",[],"A lakehouse platform with unified governance supports this. With tools such as Unity Catalog, data classification, and attribute-based access control, you can create a single source of truth that every agent respects. Instead of each team copying data into private stores, the agent reads from one governed layer, with one shared permission model. That is how you keep AI agents from becoming shadows that no one can see or control.",[],{"_key":974,"_type":99,"children":975,"markDefs":980,"style":182},"0f14b81f91d9",[976],{"_key":977,"_type":103,"marks":978,"text":979},"fa65296d2458",[],"Designing Enterprise AI Agents Around Governed Lakehouse Data",[],{"_key":982,"_type":99,"children":983,"markDefs":988,"style":107},"956143669ec3",[984],{"_key":985,"_type":103,"marks":986,"text":987},"1d744c70196c",[],"Good design starts with the business outcome, not the model. Before picking a model family or an agent framework, it helps to map out which \"colleagues\" you actually want:",[],{"_key":990,"_type":99,"children":991,"level":230,"listItem":231,"markDefs":996,"style":107},"b62e6bf9c5f9",[992],{"_key":993,"_type":103,"marks":994,"text":995},"8a14c36223d8",[],"An FP&A copilot that explains variances and builds scenarios",[],{"_key":998,"_type":99,"children":999,"level":230,"listItem":231,"markDefs":1004,"style":107},"8ee78817ba8e",[1000],{"_key":1001,"_type":103,"marks":1002,"text":1003},"948179931e86",[],"A risk investigation assistant that links cases, events, and alerts",[],{"_key":1006,"_type":99,"children":1007,"level":230,"listItem":231,"markDefs":1012,"style":107},"a1de568b8b96",[1008],{"_key":1009,"_type":103,"marks":1010,"text":1011},"d806e88f5374",[],"A supply chain planner that spots issues and suggests changes",[],{"_key":1014,"_type":99,"children":1015,"markDefs":1020,"style":107},"4bf6c9305232",[1016],{"_key":1017,"_type":103,"marks":1018,"text":1019},"4df8d20d010c",[],"For each of these, you can then list the data domains they touch, the sensitivity of that data, and any rules that apply. For example, finance data may be confidential by default, while some supply chain data can be shared more freely inside the organisation.",[],{"_key":1022,"_type":99,"children":1023,"markDefs":1028,"style":107},"eadbf1a7ea04",[1024],{"_key":1025,"_type":103,"marks":1026,"text":1027},"2b45eb9cb649",[],"Once that is clear, we design agents to query data in place, not copy it into yet another silo. Patterns that help include:",[],{"_key":1030,"_type":99,"children":1031,"level":230,"listItem":231,"markDefs":1036,"style":107},"7283e4d3213e",[1032],{"_key":1033,"_type":103,"marks":1034,"text":1035},"226c29f5bbdf",[],"Vector search on documents and tables stored in the lakehouse",[],{"_key":1038,"_type":99,"children":1039,"level":230,"listItem":231,"markDefs":1044,"style":107},"f893f2caa911",[1040],{"_key":1041,"_type":103,"marks":1042,"text":1043},"7e654f0ef234",[],"A semantic layer that exposes clear business metrics and definitions",[],{"_key":1046,"_type":99,"children":1047,"level":230,"listItem":231,"markDefs":1052,"style":107},"2ff5158510d9",[1048],{"_key":1049,"_type":103,"marks":1050,"text":1051},"27dd3ad49445",[],"Governed SQL endpoints that agents call instead of raw queries",[],{"_key":1054,"_type":99,"children":1055,"markDefs":1060,"style":107},"2ae5823ed2ad",[1056],{"_key":1057,"_type":103,"marks":1058,"text":1059},"f92ab60e2cb9",[],"All of this should pass through Unity Catalog, with PII masking, row-level filters, and policy-as-code. Every time the agent wants to retrieve or change data, its request is checked against the rules. If a user does not have access, the agent does not get access either.",[],{"_key":1062,"_type":99,"children":1063,"markDefs":1068,"style":107},"c8c227ed2292",[1064],{"_key":1065,"_type":103,"marks":1066,"text":1067},"4734604226a2",[],"Observability is just as important. We log prompts, retrieved data sets, model versions, and outputs into a governed audit trail. This lets teams:",[],{"_key":1070,"_type":99,"children":1071,"level":230,"listItem":231,"markDefs":1076,"style":107},"83f04ba3e3ec",[1072],{"_key":1073,"_type":103,"marks":1074,"text":1075},"950981804dea",[],"Trace how an answer was built",[],{"_key":1078,"_type":99,"children":1079,"level":230,"listItem":231,"markDefs":1084,"style":107},"ac6b6740d730",[1080],{"_key":1081,"_type":103,"marks":1082,"text":1083},"1a29ec502c4e",[],"Tune performance and reduce hallucinations",[],{"_key":1086,"_type":99,"children":1087,"level":230,"listItem":231,"markDefs":1092,"style":107},"37727dd5c18d",[1088],{"_key":1089,"_type":103,"marks":1090,"text":1091},"235390856154",[],"Provide clear records for internal and external reviews",[],{"_key":1094,"_type":99,"children":1095,"markDefs":1100,"style":107},"4d755c0e157a",[1096],{"_key":1097,"_type":103,"marks":1098,"text":1099},"dc97944ed1e8",[],"That way, AI agents behave less like a black box and more like any other well-governed system in the organisation.",[],{"_key":1102,"_type":99,"children":1103,"markDefs":1108,"style":182},"a29966d6e45e",[1104],{"_key":1105,"_type":103,"marks":1106,"text":1107},"69005e71e0a1",[],"Operational Governance for Production-Grade Enterprise Agents",[],{"_key":1110,"_type":99,"children":1111,"markDefs":1116,"style":107},"6ea01f33a9d5",[1112],{"_key":1113,"_type":103,"marks":1114,"text":1115},"fa6cb738093b",[],"Many organisations have good controls for data, but fewer have the same discipline for prompts, tools, and agents. Once an agent handles real work, it needs the same care as a trading system, an ERP platform, or an HR system.",[],{"_key":1118,"_type":99,"children":1119,"markDefs":1124,"style":107},"3fa9d0393b33",[1120],{"_key":1121,"_type":103,"marks":1122,"text":1123},"e055eeb1b208",[],"Operational governance covers things like:",[],{"_key":1126,"_type":99,"children":1127,"level":230,"listItem":231,"markDefs":1132,"style":107},"f7ea8e8fff7c",[1128],{"_key":1129,"_type":103,"marks":1130,"text":1131},"bae3e8f1ac72",[],"Change management for prompts, tools, and workflows",[],{"_key":1134,"_type":99,"children":1135,"level":230,"listItem":231,"markDefs":1140,"style":107},"93d6d4c91132",[1136],{"_key":1137,"_type":103,"marks":1138,"text":1139},"8773cc8513bf",[],"Approval paths before new capabilities go live",[],{"_key":1142,"_type":99,"children":1143,"level":230,"listItem":231,"markDefs":1148,"style":107},"a89a02cd337d",[1144],{"_key":1145,"_type":103,"marks":1146,"text":1147},"9b490748015b",[],"Versioning, so you can roll back quickly if something breaks",[],{"_key":1150,"_type":99,"children":1151,"markDefs":1156,"style":107},"6adbc4a58a4e",[1152],{"_key":1153,"_type":103,"marks":1154,"text":1155},"47adfd5f94f6",[],"Continuous evaluation is also key. Clear KPIs keep people aligned on what \"good\" looks like. Typical measures might include:",[],{"_key":1158,"_type":99,"children":1159,"level":230,"listItem":231,"markDefs":1164,"style":107},"1b04c33c2adc",[1160],{"_key":1161,"_type":103,"marks":1162,"text":1163},"88bdb1179118",[],"Accuracy for specific question types",[],{"_key":1166,"_type":99,"children":1167,"level":230,"listItem":231,"markDefs":1172,"style":107},"6271edd5c575",[1168],{"_key":1169,"_type":103,"marks":1170,"text":1171},"8ba5863f5060",[],"Latency, so teams are not left waiting for answers",[],{"_key":1174,"_type":99,"children":1175,"level":230,"listItem":231,"markDefs":1180,"style":107},"2ddd7848a7f8",[1176],{"_key":1177,"_type":103,"marks":1178,"text":1179},"5a0151434630",[],"Policy violations, such as blocked data access attempts",[],{"_key":1182,"_type":99,"children":1183,"level":230,"listItem":231,"markDefs":1188,"style":107},"81365ab777eb",[1184],{"_key":1185,"_type":103,"marks":1186,"text":1187},"0d6c1efef034",[],"User satisfaction from short in-context feedback prompts",[],{"_key":1190,"_type":99,"children":1191,"markDefs":1196,"style":107},"f3a3d0b8508c",[1192],{"_key":1193,"_type":103,"marks":1194,"text":1195},"df4396c32570",[],"These can be backed by automated tests, synthetic workloads, and red-teaming to probe for risky behaviour.",[],{"_key":1198,"_type":99,"children":1199,"markDefs":1204,"style":107},"49754d04d535",[1200],{"_key":1201,"_type":103,"marks":1202,"text":1203},"aea722cea855",[],"Regulation is another part of daily life for larger enterprises. Governance for AI agents should map to existing frameworks, such as GDPR requirements on personal data, ISO 27001 controls for security, or sector rules in finance, healthcare, and the public sector. When year-end reporting and audits arrive, it helps a lot if your data, models, and agents all share the same catalog, lineage, and control plane.",[],{"_key":1206,"_type":99,"children":1207,"markDefs":1212,"style":107},"66bb6a46ab17",[1208],{"_key":1209,"_type":103,"marks":1210,"text":1211},"52b87ac3a4f1",[],"On Databricks, we see value in CI/CD pipelines for agent components, centralised cataloguing of models and features, and monitoring dashboards that cover data quality, model health, and agent interactions in one view. Cosmos Thrace focuses on putting these building blocks together in a way that matches each client's risk appetite and operating model, rather than adding more scattered tools.",[],{"_key":1214,"_type":99,"children":1215,"markDefs":1220,"style":182},"9995208cfec3",[1216],{"_key":1217,"_type":103,"marks":1218,"text":1219},"753d57b78609",[],"From Pilots to a Scaled Enterprise AI Agent Ecosystem",[],{"_key":1222,"_type":99,"children":1223,"markDefs":1228,"style":107},"4eda93e9fb6b",[1224],{"_key":1225,"_type":103,"marks":1226,"text":1227},"6dc5ecc48393",[],"Many teams are stuck in pilot mode. They have a successful proof of concept, but struggle to repeat it safely across the wider business. The pattern that works best is simple: start with a strong lakehouse core, then grow from there in clear steps.",[],{"_key":1230,"_type":99,"children":1231,"markDefs":1236,"style":107},"639da4d5baa0",[1232],{"_key":1233,"_type":103,"marks":1234,"text":1235},"2b3120bedc73",[],"A typical path looks like this:",[],{"_key":1238,"_type":99,"children":1239,"level":230,"listItem":231,"markDefs":1244,"style":107},"e7804d05e979",[1240],{"_key":1241,"_type":103,"marks":1242,"text":1243},"cd3e0123cc17",[],"Build or modernise the governed lakehouse foundation",[],{"_key":1246,"_type":99,"children":1247,"level":230,"listItem":231,"markDefs":1252,"style":107},"caebd79111f0",[1248],{"_key":1249,"_type":103,"marks":1250,"text":1251},"808dc6ed3b6e",[],"Deliver one or two high-value agents for priority functions",[],{"_key":1254,"_type":99,"children":1255,"level":230,"listItem":231,"markDefs":1260,"style":107},"94f8beffd85f",[1256],{"_key":1257,"_type":103,"marks":1258,"text":1259},"33fd0c5df0ff",[],"Reuse the same governance patterns for the next wave of agents",[],{"_key":1262,"_type":99,"children":1263,"markDefs":1268,"style":107},"1c4411106e68",[1264],{"_key":1265,"_type":103,"marks":1266,"text":1267},"d1a43b6b4824",[],"The goal is federation, not fragmentation. Different business units should be free to create domain-specific agents, as long as they stay on the shared platform, catalog, and policy framework. This reduces \"agent sprawl\", where each unit invents its own standards and risk grows quietly in the background.",[],{"_key":1270,"_type":99,"children":1271,"markDefs":1276,"style":107},"558f8a3c7399",[1272],{"_key":1273,"_type":103,"marks":1274,"text":1275},"56d1f7eaf91f",[],"Reusable components make this easier:",[],{"_key":1278,"_type":99,"children":1279,"level":230,"listItem":231,"markDefs":1284,"style":107},"b5da691d31a0",[1280],{"_key":1281,"_type":103,"marks":1282,"text":1283},"2bb6263291d4",[],"Shared retrieval and prompt patterns",[],{"_key":1286,"_type":99,"children":1287,"level":230,"listItem":231,"markDefs":1292,"style":107},"82e83d8592ee",[1288],{"_key":1289,"_type":103,"marks":1290,"text":1291},"f043e579abfe",[],"Approved tools for ticketing, ERP, CRM, and communication platforms",[],{"_key":1294,"_type":99,"children":1295,"level":230,"listItem":231,"markDefs":1300,"style":107},"26ee7be4461a",[1296],{"_key":1297,"_type":103,"marks":1298,"text":1299},"7a630684ea54",[],"Pre-vetted model families that pass baseline governance checks",[],{"_key":1302,"_type":99,"children":1303,"markDefs":1308,"style":107},"72556dc6eee2",[1304],{"_key":1305,"_type":103,"marks":1306,"text":1307},"3e2fa2036e37",[],"Seasonal cycles can help with planning. For example, finance teams often test new agents ahead of budgeting periods, while retail and logistics teams may align trials with peak trading seasons. Quick, clear wins during these periods can show real value and make it easier to secure long-term executive support.",[],{"_key":1310,"_type":99,"children":1311,"markDefs":1316,"style":182},"df55485116fd",[1312],{"_key":1313,"_type":103,"marks":1314,"text":1315},"8c707e747eb2",[],"Making Governance Your Competitive Edge for Enterprise AI Agents",[],{"_key":1318,"_type":99,"children":1319,"markDefs":1324,"style":107},"727777d700af",[1320],{"_key":1321,"_type":103,"marks":1322,"text":1323},"5f16227d642c",[],"The organisations that will really win with enterprise AI agents are not the ones with the flashiest demos. They are the ones that treat governance as a first-class design choice, and then automate as much of it as they can. A well-governed lakehouse, a central catalog, shared policies, and agent architectures that respect those controls by design, together form a powerful base.",[],{"_key":1326,"_type":99,"children":1327,"markDefs":1332,"style":107},"b601c6cb4be5",[1328],{"_key":1329,"_type":103,"marks":1330,"text":1331},"ec81a90ce8ec",[],"At Cosmos Thrace, as a Databricks Select Partner, we focus on that base. We help enterprises unify data, analytics, and AI into a lakehouse that supports serious agentic workloads, from early strategy and migration all the way through to production-grade machine learning and complex AI agents. With a strong governance core in place, organisations can move with confidence into the more advanced multi-agent workflows and autonomous decision support, without losing control or compliance, whatever the weather or season brings next.",[],{"_key":1334,"_type":99,"children":1335,"markDefs":1339,"style":182},"00f99680c914",[1336],{"_key":1337,"_type":103,"marks":1338,"text":767},"35d81b90385a",[],[],{"_key":1341,"_type":99,"children":1342,"markDefs":1363,"style":107},"11774d3988ea",[1343,1347,1352,1356,1360],{"_key":1344,"_type":103,"marks":1345,"text":1346},"188807b3bbd6",[],"If you are ready to explore how our ",{"_key":1348,"_type":103,"marks":1349,"text":1351},"998a84b38bd8",[1350],"2ae81215ef48","enterprise AI agents",{"_key":1353,"_type":103,"marks":1354,"text":1355},"94f895465cd1",[]," can streamline operations and unlock new value, we are here to help you define the right approach. 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Enterprise AI Agents on the Databricks Lakehouse",[],{"_key":3034,"_type":99,"children":3035,"markDefs":3040,"style":107},"7aec7c48f3da",[3036],{"_key":3037,"_type":103,"marks":3038,"text":3039},"eb95b6c2662e",[],"Enterprise AI agents are starting to move out of labs and into real work. Leaders are no longer asking if they should use AI; they are asking how it can safely change productivity, cost and revenue. That shift sounds exciting, but it also raises a hard question: how do we turn chatty demos into reliable helpers that actually move business KPIs?",[],{"_key":3042,"_type":99,"children":3043,"markDefs":3048,"style":107},"fbe7c206f8e3",[3044],{"_key":3045,"_type":103,"marks":3046,"text":3047},"27cc2ded26a2",[],"In this article, we look at what goes wrong with many early AI agents, why a governed data core matters, and how the Databricks Lakehouse can act as a strong base. 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That is where a lakehouse comes in, joining analytics and AI on one governed platform instead of spreading agents across random tools.",[],{"_key":3115,"_type":99,"children":3116,"markDefs":3121,"style":107},"5f3c62cf4705",[3117],{"_key":3118,"_type":103,"marks":3119,"text":3120},"21073467600a",[],"As planning cycles come around again and new AI rules start to appear, it is a good time to rethink AI agent strategy. The question shifts from \"what could we build\" to \"what should we trust, scale and fund.\"",[],{"_key":3123,"_type":99,"children":3124,"markDefs":3129,"style":182},"44317b963f3c",[3125],{"_key":3126,"_type":103,"marks":3127,"text":3128},"b761e33b80c5",[],"Why AI Agents Fail Without a Governed Data Core",[],{"_key":3131,"_type":99,"children":3132,"markDefs":3137,"style":107},"596fa722e762",[3133],{"_key":3134,"_type":103,"marks":3135,"text":3136},"cbfaff772f35",[],"When AI agents fail, it is rarely because the model is not clever enough. It is usually because the data and governance behind the agent are weak.",[],{"_key":3139,"_type":99,"children":3140,"markDefs":3145,"style":107},"e9e6199dbb38",[3141],{"_key":3142,"_type":103,"marks":3143,"text":3144},"8284c6c0a3d0",[],"Typical failure patterns include:",[],{"_key":3147,"_type":99,"children":3148,"level":230,"listItem":231,"markDefs":3153,"style":107},"0e6cec3b4963",[3149],{"_key":3150,"_type":103,"marks":3151,"text":3152},"6aaa1a1509b5",[],"Hallucinations because context is thin or wrong",[],{"_key":3155,"_type":99,"children":3156,"level":230,"listItem":231,"markDefs":3161,"style":107},"beedddc90b68",[3157],{"_key":3158,"_type":103,"marks":3159,"text":3160},"c14968842378",[],"Brittle links to legacy warehouses or exports",[],{"_key":3163,"_type":99,"children":3164,"level":230,"listItem":231,"markDefs":3169,"style":107},"6890ae7f2975",[3165],{"_key":3166,"_type":103,"marks":3167,"text":3168},"ccbfa7f80c6d",[],"Siloed data that blocks end-to-end task automation",[],{"_key":3171,"_type":99,"children":3172,"level":230,"listItem":231,"markDefs":3177,"style":107},"232f81529bd1",[3173],{"_key":3174,"_type":103,"marks":3175,"text":3176},"ce8ca4f9f6b1",[],"No audit trail of who did what, when, and with which prompt",[],{"_key":3179,"_type":99,"children":3180,"markDefs":3185,"style":107},"3fb6259b666b",[3181],{"_key":3182,"_type":103,"marks":3183,"text":3184},"5d1babf578fe",[],"Risk, legal and compliance teams worry about gaps like missing lineage, inconsistent access rules, and unmanaged prompt and model changes. If no one can explain why an agent gave a certain answer, it is hard to approve it for real work.",[],{"_key":3187,"_type":99,"children":3188,"markDefs":3193,"style":107},"5cb686c536e4",[3189],{"_key":3190,"_type":103,"marks":3191,"text":3192},"1e50a5ac5181",[],"A lakehouse architecture helps by bringing:",[],{"_key":3195,"_type":99,"children":3196,"level":230,"listItem":231,"markDefs":3201,"style":107},"ae65cd50ca82",[3197],{"_key":3198,"_type":103,"marks":3199,"text":3200},"5c5fecdb7258",[],"Unified storage and compute for analytics and AI",[],{"_key":3203,"_type":99,"children":3204,"level":230,"listItem":231,"markDefs":3209,"style":107},"99496792f0f4",[3205],{"_key":3206,"_type":103,"marks":3207,"text":3208},"2aa4f52ae413",[],"Fine-grained security, so access follows business policy",[],{"_key":3211,"_type":99,"children":3212,"level":230,"listItem":231,"markDefs":3217,"style":107},"e3e9ef3c4162",[3213],{"_key":3214,"_type":103,"marks":3215,"text":3216},"b3e23c3b9f41",[],"Delta Lake reliability and data quality checks",[],{"_key":3219,"_type":99,"children":3220,"level":230,"listItem":231,"markDefs":3225,"style":107},"70ee1b9d3f8a",[3221],{"_key":3222,"_type":103,"marks":3223,"text":3224},"f3733c8df6c7",[],"Clear separation between data products, feature store and agent orchestration",[],{"_key":3227,"_type":99,"children":3228,"markDefs":3233,"style":107},"33e19f054abb",[3229],{"_key":3230,"_type":103,"marks":3231,"text":3232},"fb4956c2b11d",[],"This separation is key. Agents should not be wired straight into application databases or hidden spreadsheets. Instead, they should work on well-defined, governed data products. That does not slow innovation, it makes it repeatable. Once one agent can safely work with a governed customer data product, others can reuse the same pattern.",[],{"_key":3235,"_type":99,"children":3236,"markDefs":3241,"style":182},"78860b31c131",[3237],{"_key":3238,"_type":103,"marks":3239,"text":3240},"3bd46e5dbaaa",[],"Designing Enterprise AI Agents on Databricks Lakehouse",[],{"_key":3243,"_type":99,"children":3244,"markDefs":3249,"style":107},"a38c04fadc64",[3245],{"_key":3246,"_type":103,"marks":3247,"text":3248},"1889ec8ff50c",[],"On Databricks, we can design AI agents on top of the lakehouse in a clear, layered way. At a high level, a reference flow looks like this:",[],{"_key":3251,"_type":99,"children":3252,"level":230,"listItem":231,"markDefs":3257,"style":107},"8a72be96547f",[3253],{"_key":3254,"_type":103,"marks":3255,"text":3256},"d9998df3976e",[],"Ingest raw data into Delta Lake",[],{"_key":3259,"_type":99,"children":3260,"level":230,"listItem":231,"markDefs":3265,"style":107},"462a3eb3e2fd",[3261],{"_key":3262,"_type":103,"marks":3263,"text":3264},"35c86c81e2b8",[],"Curate bronze, silver and gold tables for clean business views",[],{"_key":3267,"_type":99,"children":3268,"level":230,"listItem":231,"markDefs":3273,"style":107},"aaba7ab6b205",[3269],{"_key":3270,"_type":103,"marks":3271,"text":3272},"58b9d308f5de",[],"Index relevant text and tables for vector search and retrieval-augmented generation",[],{"_key":3275,"_type":99,"children":3276,"level":230,"listItem":231,"markDefs":3281,"style":107},"09d4c916f5bd",[3277],{"_key":3278,"_type":103,"marks":3279,"text":3280},"717985d6a65a",[],"Orchestrate agents with workflows, events and tools that call APIs, SQL or notebooks",[],{"_key":3283,"_type":99,"children":3284,"markDefs":3289,"style":107},"c4d9d61d9340",[3285],{"_key":3286,"_type":103,"marks":3287,"text":3288},"2ca0bd11f36e",[],"Databricks native tools make this stack feel joined up. Unity Catalog gives central governance for data, models and AI assets. MLflow keeps track of models and experiments. Feature Store supports shared features. Mosaic AI (where available) ties together LLMs, prompts, tools and evaluations. Delta Live Tables keeps pipelines reliable and monitored.",[],{"_key":3291,"_type":99,"children":3292,"markDefs":3297,"style":107},"c92ec587bc15",[3293],{"_key":3294,"_type":103,"marks":3295,"text":3296},"0aaaabc94edc",[],"When we design agents on top of that, some clear principles help:",[],{"_key":3299,"_type":99,"children":3300,"level":230,"listItem":231,"markDefs":3305,"style":107},"daf453b067f8",[3301],{"_key":3302,"_type":103,"marks":3303,"text":3304},"4e1c41f55be7",[],"Break big tasks into smaller, well-defined steps",[],{"_key":3307,"_type":99,"children":3308,"level":230,"listItem":231,"markDefs":3313,"style":107},"42d91c24789b",[3309],{"_key":3310,"_type":103,"marks":3311,"text":3312},"6775627ce376",[],"Give agents tools, not direct database access, so actions are controlled",[],{"_key":3315,"_type":99,"children":3316,"level":230,"listItem":231,"markDefs":3321,"style":107},"4c9aa3a8ec0a",[3317],{"_key":3318,"_type":103,"marks":3319,"text":3320},"ed1498f186fd",[],"Use role-based access that follows business domains and data sensitivity",[],{"_key":3323,"_type":99,"children":3324,"level":230,"listItem":231,"markDefs":3329,"style":107},"b07837ea47d7",[3325],{"_key":3326,"_type":103,"marks":3327,"text":3328},"8da2414a802b",[],"Set guardrails so agents know what they must not do",[],{"_key":3331,"_type":99,"children":3332,"markDefs":3337,"style":107},"7f1d73f93cbb",[3333],{"_key":3334,"_type":103,"marks":3335,"text":3336},"b78500ad1fc8",[],"Observability is just as important. We need to log prompts, responses, tool calls and user feedback, then review them. Quality dashboards and evaluation frameworks can spot drift, bias and new failure modes early, before they hit core processes.",[],{"_key":3339,"_type":99,"children":3340,"markDefs":3345,"style":107},"9aa482e72687",[3341],{"_key":3342,"_type":103,"marks":3343,"text":3344},"e97c11dc1f92",[],"Over time, repeated patterns can be turned into blueprints and accelerators. That shortens the path from first proof of concept to a production agent that works inside a governed platform instead of outside it.",[],{"_key":3347,"_type":99,"children":3348,"markDefs":3353,"style":182},"a946a71f325f",[3349],{"_key":3350,"_type":103,"marks":3351,"text":3352},"c2056c145915",[],"High Impact Use Cases for Enterprise AI Agents",[],{"_key":3355,"_type":99,"children":3356,"markDefs":3361,"style":107},"8064541dd169",[3357],{"_key":3358,"_type":103,"marks":3359,"text":3360},"f8db8465f0a4",[],"Once the lakehouse is ready, the real question is which problems to tackle first. Some cross-functional use cases are especially promising:",[],{"_key":3363,"_type":99,"children":3364,"level":230,"listItem":231,"markDefs":3369,"style":107},"3f155d1cf837",[3365],{"_key":3366,"_type":103,"marks":3367,"text":3368},"b6985f388871",[],"Assisted analytics, where staff can ask questions over governed data and get explainable answers",[],{"_key":3371,"_type":99,"children":3372,"level":230,"listItem":231,"markDefs":3377,"style":107},"249ed2e270f4",[3373],{"_key":3374,"_type":103,"marks":3375,"text":3376},"c53625ec4a51",[],"AI powered data quality triage, with agents flagging issues, suggesting fixes and opening tickets",[],{"_key":3379,"_type":99,"children":3380,"level":230,"listItem":231,"markDefs":3385,"style":107},"54fb26441a68",[3381],{"_key":3382,"_type":103,"marks":3383,"text":3384},"ea3263f28edd",[],"Intelligent documentation agents for data and BI assets, making it easier to find and trust reports",[],{"_key":3387,"_type":99,"children":3388,"markDefs":3393,"style":107},"972a4597e497",[3389],{"_key":3390,"_type":103,"marks":3391,"text":3392},"9c3e3f69ef24",[],"Operational teams can gain from agents that do more than answer questions. For example, in supply chain, agents can watch for exceptions, trigger playbooks and call APIs to update systems. In incident response, agents can suggest next steps and link straight to runbooks. Finance teams can use agents to support the period close, chasing missing items and summarising status.",[],{"_key":3395,"_type":99,"children":3396,"markDefs":3401,"style":107},"a9f8b3ea24f9",[3397],{"_key":3398,"_type":103,"marks":3399,"text":3400},"479139c60145",[],"Knowledge-heavy functions also stand out. Legal and compliance teams can query current policies grounded in lakehouse data. R&D teams can use research companions that mix internal and external sources in a safe way. Customer support copilots can blend product knowledge, case history and policy in one place.",[],{"_key":3403,"_type":99,"children":3404,"markDefs":3409,"style":107},"05965c0d8753",[3405],{"_key":3406,"_type":103,"marks":3407,"text":3408},"870bea407d36",[],"Seasonal timing matters. Many organisations use the middle of the year for planning and budgeting. That can be a smart window to test AI agents around forecasting, planning, and reporting processes, giving time for learning cycles before peak trading or reporting periods. Each use case should be tied to clear KPIs such as cycle time, case deflection, analyst time saved or revenue at risk protected, all under a shared risk and ownership model.",[],{"_key":3411,"_type":99,"children":3412,"markDefs":3417,"style":182},"6c68038b9300",[3413],{"_key":3414,"_type":103,"marks":3415,"text":3416},"76197827e399",[],"Building a Governed AI Agent Operating Model",[],{"_key":3419,"_type":99,"children":3420,"markDefs":3425,"style":107},"3d9c1c11968d",[3421],{"_key":3422,"_type":103,"marks":3423,"text":3424},"b206d532c46b",[],"Technology alone is not enough. 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Databricks Cost Optimisation Without Slowing Teams",[],{"_key":3634,"_type":99,"children":3635,"markDefs":3640,"style":107},"86970e9b9bc1",[3636],{"_key":3637,"_type":103,"marks":3638,"text":3639},"4f491158bed2",[],"Databricks cost optimisation is not about saying no to engineers. It is about making sure every pound of spend turns into faster insight, better products, and stronger AI. When we treat costs this way, the conversation shifts from cuts and limits to smart choices and better outcomes.",[],{"_key":3642,"_type":99,"children":3643,"markDefs":3648,"style":107},"5920c6147392",[3644],{"_key":3645,"_type":103,"marks":3646,"text":3647},"2267b60093bf",[],"In this article, we will look at where Databricks spend really comes from, how lakehouse design shapes your bill, and what practical steps keep teams fast while keeping finance happy. We will keep things simple, concrete and focused on what actually works when people are busy and budgets are tight.",[],{"_key":3650,"_type":99,"children":3651,"markDefs":3656,"style":182},"4e531c6cc2a9",[3652],{"_key":3653,"_type":103,"marks":3654,"text":3655},"041609dbe31f",[],"Turn Databricks Spend Into Competitive Advantage",[],{"_key":3658,"_type":99,"children":3659,"markDefs":3664,"style":107},"ac52ad23dde0",[3660],{"_key":3661,"_type":103,"marks":3662,"text":3663},"c989dcc85275",[],"For many teams, Databricks feels like a tap: turn it on, get answers. Then the bill lands and the questions start. If the only goal is to shrink that bill, the usual response is to block, slow or restrict. That often backfires. People find workarounds, projects stall and hidden costs grow in other tools.",[],{"_key":3666,"_type":99,"children":3667,"markDefs":3672,"style":107},"2b5376cc0afe",[3668],{"_key":3669,"_type":103,"marks":3670,"text":3671},"4ee9e408347e",[],"A better way is to treat Databricks cost optimisation as a lever for advantage. When you free up spend from waste, you can:",[],{"_key":3674,"_type":99,"children":3675,"level":230,"listItem":231,"markDefs":3680,"style":107},"adf2c729c722",[3676],{"_key":3677,"_type":103,"marks":3678,"text":3679},"43c9661b07e2",[],"Fund new AI pilots without asking for extra budget",[],{"_key":3682,"_type":99,"children":3683,"level":230,"listItem":231,"markDefs":3688,"style":107},"012897376894",[3684],{"_key":3685,"_type":103,"marks":3686,"text":3687},"7c5c77bb8b4f",[],"Speed up existing data products by moving them to better patterns",[],{"_key":3690,"_type":99,"children":3691,"level":230,"listItem":231,"markDefs":3696,"style":107},"26dd9eba0a1a",[3692],{"_key":3693,"_type":103,"marks":3694,"text":3695},"dde5b5af024b",[],"Give teams headroom to experiment where it really matters",[],{"_key":3698,"_type":99,"children":3699,"markDefs":3704,"style":107},"48d65db384a4",[3700],{"_key":3701,"_type":103,"marks":3702,"text":3703},"2d3c8200f37f",[],"There is a natural tension here. Finance teams want predictability and lower bills. Engineering teams want zero friction and fast feedback. Traditional cost cutting tries to satisfy finance first and usually adds friction for engineers, with manual approvals, long reviews and hard limits. The trick is to solve for both sides at once.",[],{"_key":3706,"_type":99,"children":3707,"markDefs":3712,"style":107},"87a93867281f",[3708],{"_key":3709,"_type":103,"marks":3710,"text":3711},"e7f87362c4c7",[],"As AI adoption grows and workloads become more complex, every Databricks job, SQL query and notebook needs a clear reason to exist. Cost, performance and value need to sit in the same conversation, not in separate meetings weeks apart. That is the lens we bring as a Databricks Select Partner, focusing on modern lakehouse design, data modernisation and production AI with efficiency built in from day one.",[],{"_key":3714,"_type":99,"children":3715,"markDefs":3720,"style":182},"8bbdea01fee0",[3716],{"_key":3717,"_type":103,"marks":3718,"text":3719},"6740e0fe1b5e",[],"Get Clear on Where Databricks Costs Come From",[],{"_key":3722,"_type":99,"children":3723,"markDefs":3728,"style":107},"6f71145b1918",[3724],{"_key":3725,"_type":103,"marks":3726,"text":3727},"584beeead1cf",[],"You cannot fix what you cannot see. Databricks spend usually comes from a mix of:",[],{"_key":3730,"_type":99,"children":3731,"level":230,"listItem":231,"markDefs":3736,"style":107},"0885127572c4",[3732],{"_key":3733,"_type":103,"marks":3734,"text":3735},"4303a4f3af22",[],"Interactive clusters for notebooks and ad hoc analysis",[],{"_key":3738,"_type":99,"children":3739,"level":230,"listItem":231,"markDefs":3744,"style":107},"5b88c399d6c0",[3740],{"_key":3741,"_type":103,"marks":3742,"text":3743},"26065df97881",[],"Job clusters for scheduled ETL and production pipelines",[],{"_key":3746,"_type":99,"children":3747,"level":230,"listItem":231,"markDefs":3752,"style":107},"ce6eebb1f5bb",[3748],{"_key":3749,"_type":103,"marks":3750,"text":3751},"2f9cb9fd6ff2",[],"SQL warehouses for BI dashboards and self-service queries",[],{"_key":3754,"_type":99,"children":3755,"level":230,"listItem":231,"markDefs":3760,"style":107},"39474f5a4ae5",[3756],{"_key":3757,"_type":103,"marks":3758,"text":3759},"b66826d34517",[],"Different DBU types, from standard to high-memory or GPU",[],{"_key":3762,"_type":99,"children":3763,"level":230,"listItem":231,"markDefs":3768,"style":107},"2d289de3ee8b",[3764],{"_key":3765,"_type":103,"marks":3766,"text":3767},"82d7dacbbc50",[],"Storage, data egress and frequent reads on the same hot tables",[],{"_key":3770,"_type":99,"children":3771,"markDefs":3776,"style":107},"ef26ca49cddf",[3772],{"_key":3773,"_type":103,"marks":3774,"text":3775},"84355ad7f47e",[],"On paper, the levers look like cluster sizes, instance types and storage tiers. 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At Cosmos Thrace, we work with your team to identify quick wins as well as longer term structural improvements so you see measurable savings without sacrificing performance. To discuss your specific environment and priorities, simply ",{"_key":4214,"_type":103,"marks":4215,"text":789},"c6d5d0dc7b6c",[4216],"babffc67e85b",{"_key":4218,"_type":103,"marks":4219,"text":4220},"ccebe18b7289",[]," and we will outline a pragmatic plan tailored to your organisation.",[4222,4224],{"_key":4207,"_type":173,"href":4223},"https://cosmosthrace.com/databricks-poc-and-mvp-scoping",{"_key":4216,"_type":173,"href":798},{"_type":17,"current":4226},"master-databricks-cost-optimization-without-slowing-teams",{"_createdAt":4228,"_id":4229,"_rev":4230,"_type":72,"_updatedAt":4231,"author":4232,"category":4236,"date":4240,"description":4241,"image":4250,"name":4285,"orderRank":4286,"reviewer":4287,"sections":4302,"seo":161,"slug":4923,"tags":161},"2026-03-24T20:40:46Z","93f0555e-d56d-4637-80be-aada2dc30f1d","pbVPtgVbwyH6oOhWYlMUPo","2026-03-26T15:51:13Z",{"_createdAt":75,"_id":76,"_rev":77,"_type":78,"_updatedAt":79,"image":4233,"linkedin":85,"name":86,"orderRank":40,"position":87,"quote":88,"slug":4235},{"_type":81,"asset":4234},{"_ref":83,"_type":84},{"_type":17,"current":90},{"_createdAt":6,"_id":7,"_rev":8,"_system":4237,"_type":12,"_updatedAt":13,"name":14,"orderRank":15,"slug":4239,"uid":18},{"base":4238},{"id":7,"rev":11},{"_type":17,"current":18},"2026-03-24",[4242],{"_key":4243,"_type":99,"children":4244,"markDefs":4249,"style":107},"38b7aa6159cd",[4245],{"_key":4246,"_type":103,"marks":4247,"text":4248},"cb666a9f2305",[],"Learn why medallion architecture fails quietly and how to fix it. Silver vs Gold decision rule, Unity Catalog structure, and 3-question diagnostic from real implementations.",[],{"_type":109,"alt":4251,"asset":4252},"Databricks Medallion Architecture Best Practices",{"_createdAt":4253,"_id":4254,"_rev":4255,"_type":114,"_updatedAt":4253,"assetId":4256,"extension":116,"metadata":4257,"mimeType":153,"originalFilename":4280,"path":4281,"sha1hash":4256,"size":4282,"uploadId":4283,"url":4284},"2026-03-26T15:50:51Z","image-55807eee2be40fc47252faeef254c50dee9f6f54-1456x816-png","akK9tLbFbEeX2MBVaUyS5y","55807eee2be40fc47252faeef254c50dee9f6f54",{"_type":118,"blurHash":4258,"dimensions":4259,"hasAlpha":125,"isOpaque":126,"lqip":4260,"palette":4261,"thumbHash":4279},"M5M77U00%C~pxu}$~qI8Di-:-J_3%2spIt",{"_type":121,"aspectRatio":122,"height":123,"width":124},"data:image/png;base64,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",{"_type":129,"darkMuted":4262,"darkVibrant":4265,"dominant":4267,"lightMuted":4270,"lightVibrant":4271,"muted":4274,"vibrant":4277},{"_type":131,"background":4263,"foreground":133,"population":4264,"title":133},"#735e7d",6.3,{"_type":131,"background":4266,"foreground":133,"population":134,"title":133},"#292064",{"_type":131,"background":4268,"foreground":140,"population":4269,"title":133},"#cbbcb3",7.41,{"_type":131,"background":4268,"foreground":140,"population":4269,"title":133},{"_type":131,"background":4272,"foreground":140,"population":4273,"title":140},"#e0ddf4",2.03,{"_type":131,"background":4275,"foreground":133,"population":4276,"title":133},"#8c6f83",1.5,{"_type":131,"background":4278,"foreground":133,"population":134,"title":133},"#4f3ec0","LCgKDIKAiYiod5iYiGa5j/2nhw==","white_twisted_blocks_on_light_beige_background_--chaos_30_--a_d884fde2-d86c-4a53-83fd-e2c06fbaa07a_2.png","images/wn2c54m4/production/55807eee2be40fc47252faeef254c50dee9f6f54-1456x816.png",2567855,"mWhdeov7W7PKWNz5KjuHpCY8Zy3L3zwh","https://cdn.sanity.io/images/wn2c54m4/production/55807eee2be40fc47252faeef254c50dee9f6f54-1456x816.png","What Are the Best Practices for Databricks Medallion Architecture?","0|1000yg:",{"_createdAt":4288,"_id":4289,"_rev":4290,"_type":78,"_updatedAt":4291,"image":4292,"linkedin":4295,"name":4296,"orderRank":4297,"position":4298,"quote":4299,"slug":4300},"2026-02-17T11:29:46Z","fbd13e1c-ccb2-43e3-bb39-46f0be95b495","b26h2dVZZQ6kmNRGOHAgz9","2026-02-17T11:30:06Z",{"_type":81,"asset":4293},{"_ref":4294,"_type":84},"image-a66d04fb04d9f44747aa4ede876c3444598688c0-800x800-jpg","https://www.linkedin.com/in/mladen-vachkov/","Mladen Vachkov","0|100020:","Marketing Director","The Marketing Wizard",{"_type":17,"current":4301},"mladen-vachkov",[4303,4779,4866],{"_createdAt":4304,"_id":4305,"_key":4306,"_ref":4305,"_rev":4307,"_system":4308,"_type":168,"_updatedAt":4311,"afterTextLevel":170,"background":161,"bckg":161,"bigTextLevel":171,"button":4312,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":4313,"descriptionLevel":799,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-03-25T16:01:56Z","e9a894de-a7ca-4eb2-90df-0a8908716cb3","98d061f8257d","HDlNiVeMvqybGjkmBSJ7kN",{"base":4309},{"id":4305,"rev":4310},"CgadNFQCI8okHl5PWhtLL1","2026-04-02T08:06:56Z",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[4314,4322,4330,4338,4346,4354,4362,4370,4378,4386,4394,4402,4410,4414,4422,4430,4438,4446,4454,4471,4479,4487,4499,4507,4515,4523,4531,4539,4547,4555,4567,4579,4591,4599,4607,4615,4623,4631,4639,4647,4655,4663,4671,4679,4687,4695,4703,4711,4719,4727,4735,4743,4761],{"_key":4315,"_type":99,"children":4316,"markDefs":4321,"style":107},"0f418145def9",[4317],{"_key":4318,"_type":103,"marks":4319,"text":4320},"4190acbdb6d0",[],"The best practices for Databricks medallion architecture come down to discipline, not design. Silver should handle cleaning, conforming, and typing. Gold should handle anything that requires domain knowledge: joins, aggregations, and business logic. The architecture itself is sound. What breaks it is convenience. Engineers place logic in whatever layer they happen to be working in, and the boundaries erode over time. The fix is structural: use a domain-first Unity Catalog layout, apply the \"does it require domain knowledge?\" decision rule at every transformation, and run a regular 3-question health check on your Gold layer.",[],{"_key":4323,"_type":99,"children":4324,"markDefs":4329,"style":182},"19dc15a2ba25",[4325],{"_key":4326,"_type":103,"marks":4327,"text":4328},"5f947a832f5e",[],"TL;DR",[],{"_key":4331,"_type":99,"children":4332,"level":230,"listItem":231,"markDefs":4337,"style":107},"ba038024d76f",[4333],{"_key":4334,"_type":103,"marks":4335,"text":4336},"6f0ca9f49d8d",[],"Medallion architecture doesn't fail fast or loudly. It degrades slowly until maintenance overtakes development.",[],{"_key":4339,"_type":99,"children":4340,"level":230,"listItem":231,"markDefs":4345,"style":107},"2dea80151750",[4341],{"_key":4342,"_type":103,"marks":4343,"text":4344},"0e5e07b2b2dd",[],"The Silver vs Gold boundary should be defined by one question: does this transformation require domain knowledge?",[],{"_key":4347,"_type":99,"children":4348,"level":230,"listItem":231,"markDefs":4353,"style":107},"f164a70a714e",[4349],{"_key":4350,"_type":103,"marks":4351,"text":4352},"c75108de1845",[],"Convenience is the primary failure mechanism. \"I'm already in Silver, let me do it here\" erodes the architecture over time.",[],{"_key":4355,"_type":99,"children":4356,"level":230,"listItem":231,"markDefs":4361,"style":107},"08644490d2a9",[4357],{"_key":4358,"_type":103,"marks":4359,"text":4360},"2ce7830fa1a6",[],"Unity Catalog should be structured domain-first, not layer-first. Align catalogs to business domains, not Bronze/Silver/Gold.",[],{"_key":4363,"_type":99,"children":4364,"level":230,"listItem":231,"markDefs":4369,"style":107},"6b941d1f51bd",[4365],{"_key":4366,"_type":103,"marks":4367,"text":4368},"6015a832017f",[],"Run the 3-question diagnostic regularly: who consumes Gold? Who owns the boundary? When was Gold last updated?",[],{"_key":4371,"_type":99,"children":4372,"level":230,"listItem":231,"markDefs":4377,"style":107},"dec7d81730f6",[4373],{"_key":4374,"_type":103,"marks":4375,"text":4376},"8f8e263c7763",[],"You don't need to rebuild. You need to move the logic to the right place.",[],{"_key":4379,"_type":99,"children":4380,"markDefs":4385,"style":182},"ed0b834a8e73",[4381],{"_key":4382,"_type":103,"marks":4383,"text":4384},"3fe30fbd90b2",[],"Introduction",[],{"_key":4387,"_type":99,"children":4388,"markDefs":4393,"style":107},"bcb898ca6227",[4389],{"_key":4390,"_type":103,"marks":4391,"text":4392},"f7c9c49694a5",[],"At the Databricks Data+AI Summit 2024, one session title caught practitioners off guard: \"What's Wrong with Medallion Architecture.\" It was a fair question. By that point, the first wave of medallion implementations from 2022 and 2023 were starting to show stress fractures. Not dramatic failures. Quiet ones.",[],{"_key":4395,"_type":99,"children":4396,"markDefs":4401,"style":107},"214451c68951",[4397],{"_key":4398,"_type":103,"marks":4399,"text":4400},"7cc086eaf9d5",[],"We have seen this pattern across dozens of data platform implementations. A team sets up Bronze, Silver, and Gold. The initial structure looks clean. Six months later, data engineers spend more time on maintenance than development. Reporting tools point at Silver tables. Gold layers go stale. On paper, it still looks like a medallion architecture. In practice, it is a mess of misplaced logic and blurred boundaries.",[],{"_key":4403,"_type":99,"children":4404,"markDefs":4409,"style":107},"e5ffd95d6bf8",[4405],{"_key":4406,"_type":103,"marks":4407,"text":4408},"6581f682c1a7",[],"This article breaks down the specific practices that prevent that degradation, drawn from what we have observed across real enterprise implementations and from practitioner community discussions that have been growing louder since 2024.",[],{"_key":4411,"_type":4412,"url":4413},"588a8f17add6","videoEmbed","https://www.youtube.com/watch?v=_oQgncJEjwA",{"_key":4415,"_type":99,"children":4416,"markDefs":4421,"style":107},"93c75008de84",[4417],{"_key":4418,"_type":103,"marks":4419,"text":4420},"e3171cf50831",[],"",[],{"_key":4423,"_type":99,"children":4424,"markDefs":4429,"style":182},"ba87f52164b3",[4425],{"_key":4426,"_type":103,"marks":4427,"text":4428},"10891db71547",[],"Why Enterprise Medallion Implementations Break Down",[],{"_key":4431,"_type":99,"children":4432,"markDefs":4437,"style":107},"04d8bc291df0",[4433],{"_key":4434,"_type":103,"marks":4435,"text":4436},"4c1af944ffc3",[],"The tricky part about medallion architecture is that it is actually quite good. The Bronze/Silver/Gold pattern is intuitive, easy to explain to stakeholders, and maps cleanly to the extract-transform-load paradigm that data teams already understand. That is also what makes it dangerous.",[],{"_key":4439,"_type":99,"children":4440,"markDefs":4445,"style":107},"b6065d6d6696",[4441],{"_key":4442,"_type":103,"marks":4443,"text":4444},"be0f954bc7d0",[],"Because the pattern is simple, teams assume the execution will be simple too. It is not. The architecture does not fail because the design is wrong. It fails because convenience overrides discipline.",[],{"_key":4447,"_type":99,"children":4448,"markDefs":4453,"style":107},"b1e514f8ba32",[4449],{"_key":4450,"_type":103,"marks":4451,"text":4452},"f12eb5c3d64a",[],"Here is the pattern we see repeatedly. A data engineer is working in the Silver layer, cleaning and conforming data. They need to add a join that combines two source tables with a business rule. They know it belongs in Gold. But they are already in Silver. The pipeline is already running. \"Let me just do it here.\" One shortcut becomes two. Two becomes ten. Within a few months, Silver contains business logic, Gold is underused, and the reporting layer bypasses Gold entirely.",[],{"_key":4455,"_type":99,"children":4456,"markDefs":4470,"style":107},"e418294391c6",[4457,4461,4466],{"_key":4458,"_type":103,"marks":4459,"text":4460},"27a70670ff9a",[],"The result: ",{"_key":4462,"_type":103,"marks":4463,"text":4465},"90e19b5a8b79",[3055,4464],"highlight","70% of compute",{"_key":4467,"_type":103,"marks":4468,"text":4469},"2a07fe23b2a2",[]," can end up driven by a single materialized view. Reporting tools query Silver directly. Gold tables go weeks without being updated. Data engineers start doing more maintenance than development.",[],{"_key":4472,"_type":99,"children":4473,"markDefs":4478,"style":107},"5d339d2bd63c",[4474],{"_key":4475,"_type":103,"marks":4476,"text":4477},"2efbef783afa",[],"The community has noticed. Reddit threads like \"What the CRAP is the difference between SILVER and GOLD???\" reflect genuine confusion. Practitioners debate whether medallion is anything more than marketing rebranding of traditional data warehousing concepts. The frustration is real, but the solution is not to abandon the pattern. It is to enforce the boundaries that make it work.",[],{"_key":4480,"_type":99,"children":4481,"markDefs":4486,"style":182},"d71ac7cad61b",[4482],{"_key":4483,"_type":103,"marks":4484,"text":4485},"7771c87ecd16",[],"The Silver vs Gold Decision Rule",[],{"_key":4488,"_type":99,"children":4489,"markDefs":4498,"style":107},"a3092aac4c7f",[4490,4494],{"_key":4491,"_type":103,"marks":4492,"text":4493},"629edf8f63c0",[],"The single most useful rule we apply is this: ",{"_key":4495,"_type":103,"marks":4496,"text":4497},"114631eebdaf",[4464],"does this transformation require domain knowledge?",[],{"_key":4500,"_type":99,"children":4501,"markDefs":4506,"style":107},"dccc7c96d67b",[4502],{"_key":4503,"_type":103,"marks":4504,"text":4505},"3edefede036e",[],"If yes, it belongs in Gold. If no, it stays in Silver.",[],{"_key":4508,"_type":99,"children":4509,"markDefs":4514,"style":107},"dc7543ebbdc9",[4510],{"_key":4511,"_type":103,"marks":4512,"text":4513},"0a9126f60e67",[],"Silver handles cleaning, conforming, and typing. These are operations that any engineer can understand without knowing what the business does with the data. Deduplication, null handling, schema enforcement, timestamp standardisation. If a new hire on day one could look at the transformation and understand what it does without asking a single business question, it belongs in Silver.",[],{"_key":4516,"_type":99,"children":4517,"markDefs":4522,"style":107},"d9f403a13c0b",[4518],{"_key":4519,"_type":103,"marks":4520,"text":4521},"6d9a9106bec8",[],"Gold handles joins, aggregations, and business logic. These are operations that require understanding of how the organisation uses the data. Revenue attribution rules. Customer segmentation logic. Inventory thresholds that trigger alerts. If the transformation requires a conversation with a domain expert to understand why it exists, it belongs in Gold.",[],{"_key":4524,"_type":99,"children":4525,"markDefs":4530,"style":107},"4221a8ed5d70",[4526],{"_key":4527,"_type":103,"marks":4528,"text":4529},"bd835fbfddfa",[],"This rule eliminates the grey area that causes most medallion failures. Teams no longer debate where logic belongs. They ask one question and place it accordingly.",[],{"_key":4532,"_type":99,"children":4533,"markDefs":4538,"style":107},"18d049bd5f50",[4534],{"_key":4535,"_type":103,"marks":4536,"text":4537},"1cda2ddce591",[],"The \"new hire test\" makes it practical. Walk through each transformation in your Silver layer. For each one, ask: could someone who joined the team yesterday understand what this does and why? If the answer is no, that logic has drifted into the wrong layer.",[],{"_key":4540,"_type":99,"children":4541,"markDefs":4546,"style":182},"18443d380823",[4542],{"_key":4543,"_type":103,"marks":4544,"text":4545},"5f5ef7e92e26",[],"How to Structure Unity Catalog for Medallion Architecture",[],{"_key":4548,"_type":99,"children":4549,"markDefs":4554,"style":107},"da1d8f61ca25",[4550],{"_key":4551,"_type":103,"marks":4552,"text":4553},"e5a261258c88",[],"Unity Catalog gives you three structural options for organising your medallion layers. The choice matters more than most teams realise, because it determines how governance, access control, and discoverability scale as your data estate grows.",[],{"_key":4556,"_type":99,"children":4557,"markDefs":4566,"style":107},"cbc8c882f25b",[4558,4562],{"_key":4559,"_type":103,"marks":4560,"text":4561},"2619fc7ea091",[3055],"Option 1: Single catalog.",{"_key":4563,"_type":103,"marks":4564,"text":4565},"705e5406e64c",[]," Everything in one catalog, layers separated by schemas. Simple to start with. Does not scale. Access control becomes a nightmare when you have hundreds of tables across business domains.",[],{"_key":4568,"_type":99,"children":4569,"markDefs":4578,"style":107},"5b07ca5f21a5",[4570,4574],{"_key":4571,"_type":103,"marks":4572,"text":4573},"acf7263f949e",[3055],"Option 2: Catalog-per-layer.",{"_key":4575,"_type":103,"marks":4576,"text":4577},"94822b052d40",[]," One catalog for Bronze, one for Silver, one for Gold. This is the most common pattern we see in the wild. It is neat and intuitive. It also creates silos. Cross-layer lineage becomes harder to trace. Teams organise around layers instead of around business outcomes.",[],{"_key":4580,"_type":99,"children":4581,"markDefs":4590,"style":107},"14c8c5701570",[4582,4586],{"_key":4583,"_type":103,"marks":4584,"text":4585},"eb0b869902ad",[3055],"Option 3: Domain-first catalog.",{"_key":4587,"_type":103,"marks":4588,"text":4589},"fefe4cf81452",[]," Catalogs aligned to business domains (finance, supply chain, customer), with layers as schemas within each domain catalog. Harder to set up initially. Scales cleanly. Governance maps to organisational structure. Teams own their domain end-to-end.",[],{"_key":4592,"_type":99,"children":4593,"markDefs":4598,"style":107},"223dc73317d0",[4594],{"_key":4595,"_type":103,"marks":4596,"text":4597},"ae8c75791173",[4464],"We recommend domain-first. Every time.",[],{"_key":4600,"_type":99,"children":4601,"markDefs":4606,"style":107},"3010244fbbf1",[4602],{"_key":4603,"_type":103,"marks":4604,"text":4605},"b38a415f1f26",[],"The reason is that layer-first organisation optimises for the engineering team's view of the world. Domain-first organisation optimises for the business's view of the world. When you align catalog structure to business domains, ownership becomes natural. The finance team owns the finance catalog. Access requests make sense. Data discovery follows the way people actually think about their data, not the way it was technically processed.",[],{"_key":4608,"_type":99,"children":4609,"markDefs":4614,"style":182},"799d95a980b9",[4610],{"_key":4611,"_type":103,"marks":4612,"text":4613},"03bbefe3be93",[],"The 3-Question Medallion Health Check",[],{"_key":4616,"_type":99,"children":4617,"markDefs":4622,"style":107},"934faf828970",[4618],{"_key":4619,"_type":103,"marks":4620,"text":4621},"a57c41a1c5b4",[],"Before proposing any changes to a client's medallion architecture, we run a simple diagnostic. Three questions that tell you whether the architecture is healthy or quietly degrading.",[],{"_key":4624,"_type":99,"children":4625,"markDefs":4630,"style":107},"1f81c5cd07f5",[4626],{"_key":4627,"_type":103,"marks":4628,"text":4629},"6fe6ef6d57c2",[3055,4464],"Question 1: Who consumes your Gold layer?",[],{"_key":4632,"_type":99,"children":4633,"markDefs":4638,"style":107},"a27525ebed7a",[4634],{"_key":4635,"_type":103,"marks":4636,"text":4637},"64a3fce56cd3",[],"Check your query logs. If reporting tools, dashboards, and downstream applications primarily query Silver tables, your Gold layer is not doing its job. In a healthy medallion architecture, Gold is where consumption happens. Silver is an intermediate step, not a destination. If 70% or more of reporting queries hit Silver, the boundary has already eroded.",[],{"_key":4640,"_type":99,"children":4641,"markDefs":4646,"style":107},"f1a95e372e28",[4642],{"_key":4643,"_type":103,"marks":4644,"text":4645},"cf29e9db84c7",[3055,4464],"Question 2: Who owns the Silver/Gold boundary?",[],{"_key":4648,"_type":99,"children":4649,"markDefs":4654,"style":107},"8c1c511185cc",[4650],{"_key":4651,"_type":103,"marks":4652,"text":4653},"873ab3f727b9",[],"If the answer is \"everyone\" or \"no one,\" you have a problem. The boundary between Silver and Gold is the most important architectural decision in the entire pattern. Someone needs to own it. That means a named person or team who reviews pull requests that add transformations, who decides whether new logic belongs in Silver or Gold, and who flags drift before it compounds.",[],{"_key":4656,"_type":99,"children":4657,"markDefs":4662,"style":107},"fb88390f4781",[4658],{"_key":4659,"_type":103,"marks":4660,"text":4661},"e82591557838",[3055,4464],"Question 3: When was your Gold layer last meaningfully updated?",[],{"_key":4664,"_type":99,"children":4665,"markDefs":4670,"style":107},"7ebde15e3554",[4666],{"_key":4667,"_type":103,"marks":4668,"text":4669},"5a7400ee44b3",[],"Not a schema change. Not a column rename. A meaningful update: new business logic, new aggregation, new domain-specific transformation. If Gold has not seen a meaningful update in weeks or months, it is likely that business logic is accumulating elsewhere. Silver, the application layer, or worse, in the reporting tools themselves.",[],{"_key":4672,"_type":99,"children":4673,"markDefs":4678,"style":107},"814ed1666bc2",[4674],{"_key":4675,"_type":103,"marks":4676,"text":4677},"7f255dabb862",[],"Good answers to all three questions mean your medallion architecture is working as designed. Bad answers to any one of them mean the quiet failure is already underway.",[],{"_key":4680,"_type":99,"children":4681,"markDefs":4686,"style":182},"276d492205ef",[4682],{"_key":4683,"_type":103,"marks":4684,"text":4685},"da0885671ba1",[],"The Cosmos Thrace Perspective",[],{"_key":4688,"_type":99,"children":4689,"markDefs":4694,"style":107},"5361e6fe95d8",[4690],{"_key":4691,"_type":103,"marks":4692,"text":4693},"f40a6912c44a",[],"We have seen teams walk into organisations and propose roadmaps and big restructuring projects without first understanding the current situation. That is not how we work.",[],{"_key":4696,"_type":99,"children":4697,"markDefs":4702,"style":107},"c34d2061862a",[4698],{"_key":4699,"_type":103,"marks":4700,"text":4701},"af1209279f93",[],"What we have learned from implementing data platforms across Europe is that medallion architecture is not very different from traditional data warehousing. The layers map to staging, integration, and presentation. The concepts are proven. What breaks is not the architecture. What breaks is the discipline to maintain boundaries when it is inconvenient.",[],{"_key":4704,"_type":99,"children":4705,"markDefs":4710,"style":107},"f0a43a96ba57",[4706],{"_key":4707,"_type":103,"marks":4708,"text":4709},"a02795193376",[],"The most common mistake is not a bad technical decision. It is a cultural one. Teams that treat the Silver/Gold boundary as a suggestion rather than a contract will always end up with a degraded architecture, regardless of what tools they use.",[],{"_key":4712,"_type":99,"children":4713,"markDefs":4718,"style":107},"0d59238ef2ca",[4714],{"_key":4715,"_type":103,"marks":4716,"text":4717},"7a83a509d245",[],"The good news is that you do not have to rebuild. In most cases, the data is there, the pipelines are there, and the infrastructure is sound. You just have to move the logic to the right place. That is a refactoring project, not a migration project. It is weeks, not months.",[],{"_key":4720,"_type":99,"children":4721,"markDefs":4726,"style":107},"884ef44d7491",[4722],{"_key":4723,"_type":103,"marks":4724,"text":4725},"6f5cf78c775b",[],"We run the 3-question diagnostic at the start of every engagement where medallion architecture is involved. It takes thirty minutes. It tells us whether the architecture needs a tune-up or a structural intervention. That clarity saves our clients time and money before a single line of code is written.",[],{"_key":4728,"_type":99,"children":4729,"markDefs":4734,"style":182},"81e3a6cb001e",[4730],{"_key":4731,"_type":103,"marks":4732,"text":4733},"899f767f629f",[],"Conclusion",[],{"_key":4736,"_type":99,"children":4737,"markDefs":4742,"style":107},"375cccae058d",[4738],{"_key":4739,"_type":103,"marks":4740,"text":4741},"75d3fa6349ee",[],"Medallion architecture works when the boundaries are enforced. It fails when convenience overrides discipline. The practices that matter are not complex: use the domain knowledge rule to place logic correctly, structure Unity Catalog around business domains, and run the 3-question health check regularly.",[],{"_key":4744,"_type":99,"children":4745,"markDefs":4758,"style":107},"1b733bd69bb8",[4746,4750,4755],{"_key":4747,"_type":103,"marks":4748,"text":4749},"8de68f4c95ad",[],"If your medallion architecture feels like it is creating more work than it saves, the problem is likely not the pattern. It is where the logic lives. Download our free medallion architecture guide from ",{"_key":4751,"_type":103,"marks":4752,"text":4754},"d03933c84bce",[4753],"65a073e878bd","here",{"_key":4756,"_type":103,"marks":4757,"text":793},"8abe6b32bbfb",[],[4759],{"_key":4753,"_type":173,"href":4760},"https://cosmosthrace.com/stop-guessing-where-logic-belongs-in-your-medallion-architecture",{"_key":4762,"_type":99,"children":4763,"markDefs":4776,"style":107},"91b830431a77",[4764,4768,4773],{"_key":4765,"_type":103,"marks":4766,"text":4767},"ccb554ffbf39",[],"Cosmos Thrace is a Databricks Silver Partner that specialises in exactly this kind of diagnostic and remediation work. If you want to talk through your medallion architecture, reach out at ",{"_key":4769,"_type":103,"marks":4770,"text":4772},"cc1e9ba93174",[4771],"8cfcf6060561","hi@cosmosthrace.com",{"_key":4774,"_type":103,"marks":4775,"text":793},"666da8b53fdf",[],[4777],{"_key":4771,"_type":173,"href":4778},"mailto:hi@cosmosthrace.com",{"_createdAt":4780,"_id":4781,"_key":4782,"_ref":4781,"_rev":4783,"_system":4784,"_type":4787,"_updatedAt":4788,"accordion":4789,"afterTextLevel":170,"background":161,"bckg":161,"bigText":4863,"bigTextLevel":171,"button":4864,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":161,"descriptionLevel":799,"image":161,"images":161,"links":161,"panelTitle":4865,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-03-25T16:11:45Z","4f2979b5-53bc-4b19-81fc-a31d23746278","9e9da79f7abb","akK9tLbFbEeX2MBVaUqi9z",{"base":4785},{"id":4781,"rev":4786},"pbVPtgVbwyH6oOhWYlF90m","accordionSection","2026-03-26T15:39:54Z",{"items":4790},[4791,4803,4815,4827,4839,4851],{"_key":4792,"description":4793,"title":4802},"7c6434dc7ba6",[4794],{"_key":4795,"_type":99,"children":4796,"markDefs":4801,"style":107},"f799171d7da3",[4797],{"_key":4798,"_type":103,"marks":4799,"text":4800},"f3b248f31891",[],"Silver handles cleaning, conforming, and typing. These are generic data quality operations that do not require business context. Gold handles joins, aggregations, and business logic that require domain knowledge. The simplest test: if a new hire cannot understand the transformation without asking a business question, it belongs in Gold.",[],"What is the difference between Silver and Gold in medallion architecture?",{"_key":4804,"description":4805,"title":4814},"8b06746529b3",[4806],{"_key":4807,"_type":99,"children":4808,"markDefs":4813,"style":107},"c5adc2a02daf",[4809],{"_key":4810,"_type":103,"marks":4811,"text":4812},"e4af92a43635",[],"Check three things. First, look at your query logs. If most reporting queries hit Silver instead of Gold, the boundary has eroded. Second, check who owns the Silver/Gold boundary. If no one has explicit ownership, drift is inevitable. Third, check when Gold was last meaningfully updated. Stale Gold layers indicate business logic is accumulating elsewhere.",[],"How do I know if my medallion architecture is broken?",{"_key":4816,"description":4817,"title":4826},"74a2574174c0",[4818],{"_key":4819,"_type":99,"children":4820,"markDefs":4825,"style":107},"dabf409669ad",[4821],{"_key":4822,"_type":103,"marks":4823,"text":4824},"a8231b0d08a1",[],"We recommend a domain-first catalog structure, where each catalog aligns to a business domain (finance, supply chain, customer) with layers as schemas within each domain. This scales better than a single catalog or catalog-per-layer approach because governance maps to organisational structure and teams own their domain end-to-end.",[],"Should I use one Unity Catalog or multiple catalogs for medallion architecture?",{"_key":4828,"description":4829,"title":4838},"19ff677c5e2f",[4830],{"_key":4831,"_type":99,"children":4832,"markDefs":4837,"style":107},"fbd35ebc1e46",[4833],{"_key":4834,"_type":103,"marks":4835,"text":4836},"fc8115754a39",[],"The concepts are closely related. Bronze maps to staging, Silver to integration, Gold to presentation. The medallion pattern adds the lakehouse context: schema evolution, Delta format, Unity Catalog governance, and streaming capabilities. But the discipline required is the same discipline that made traditional data warehousing work.",[],"Is medallion architecture just traditional data warehousing?",{"_key":4840,"description":4841,"title":4850},"c8386f2fe66d",[4842],{"_key":4843,"_type":99,"children":4844,"markDefs":4849,"style":107},"39c4ac6758af",[4845],{"_key":4846,"_type":103,"marks":4847,"text":4848},"5664091a6fb2",[],"In most cases, you do not need to rebuild. The data and infrastructure are already in place. The fix is moving misplaced logic from Silver to Gold. This is a refactoring project, not a migration. Depending on the size of the estate, it takes weeks rather than months. The 3-question diagnostic takes about thirty minutes and tells you the scope.",[],"How long does it take to fix a broken medallion architecture?",{"_key":4852,"description":4853,"title":4862},"461182b4392b",[4854],{"_key":4855,"_type":99,"children":4856,"markDefs":4861,"style":107},"b2368d28c800",[4857],{"_key":4858,"_type":103,"marks":4859,"text":4860},"749ab3d56b7e",[],"Convenience. Engineers place business logic in Silver because they are already working there. One shortcut compounds into ten. The architecture degrades slowly rather than failing dramatically. This is why explicit boundary ownership and regular health checks matter more than the initial design.",[],"What is the most common cause of medallion architecture failure?","What people ask about Medallion Architecture",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},"FAQ",{"_createdAt":4867,"_id":4868,"_key":4869,"_ref":4868,"_rev":4870,"_type":168,"_updatedAt":4871,"afterTextLevel":170,"background":161,"bckg":161,"bigTextLevel":171,"button":4872,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":4873,"descriptionLevel":799,"image":161,"images":161,"links":161,"panelTitle":4880,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-03-25T16:14:29Z","42fea55b-8923-446c-8066-134e04ca17cb","f62788160d3e","zpNAPfmzgy9V2WUZNdMFor","2026-03-25T16:15:10Z",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[4874,4882,4891,4899,4907,4915],{"_key":4875,"_type":99,"children":4876,"markDefs":4881,"style":182},"024ab17109a0",[4877],{"_key":4878,"_type":103,"marks":4879,"text":4880},"313afc8ccb14",[],"Sources",[],{"_key":4883,"_type":99,"children":4884,"level":230,"listItem":4889,"markDefs":4890,"style":107},"767e1a559d59",[4885],{"_key":4886,"_type":103,"marks":4887,"text":4888},"404e58425cfb",[],"Databricks Data+AI Summit 2024 — \"What's Wrong with Medallion Architecture\" session. Acknowledged that companies regret the layering of their lake when boundaries are not maintained.","number",[],{"_key":4892,"_type":99,"children":4893,"level":230,"listItem":4889,"markDefs":4898,"style":107},"dfb6b0f472c0",[4894],{"_key":4895,"_type":103,"marks":4896,"text":4897},"9a66c6c96f2e",[],"Reddit r/databricks — Community discussion: \"What the CRAP is the difference between SILVER and GOLD???\" Thread reflects widespread practitioner confusion about layer boundaries.",[],{"_key":4900,"_type":99,"children":4901,"level":230,"listItem":4889,"markDefs":4906,"style":107},"50da747c3671",[4902],{"_key":4903,"_type":103,"marks":4904,"text":4905},"6c05d6658a03",[],"Daniel Beach — \"This so called 'Medallion Architecture' is NOTHING more than Marketing Speak.\" Practitioner blog critique comparing medallion to traditional data warehousing patterns.",[],{"_key":4908,"_type":99,"children":4909,"level":230,"listItem":4889,"markDefs":4914,"style":107},"abee73505510",[4910],{"_key":4911,"_type":103,"marks":4912,"text":4913},"cd682c772014",[],"Databricks documentation — Unity Catalog best practices for multi-layer data architectures. Covers catalog, schema, and table organisation patterns.",[],{"_key":4916,"_type":99,"children":4917,"level":230,"listItem":4889,"markDefs":4922,"style":107},"e4c756043aa1",[4918],{"_key":4919,"_type":103,"marks":4920,"text":4921},"86fa5165803a",[],"Cosmos Thrace implementation experience — Patterns observed across dozens of data platform implementations in Financial Services, Manufacturing, and Retail across Europe.",[],{"_type":17,"current":4924},"databricks-medallion-architecture-best-practices",{"_createdAt":4926,"_id":4927,"_rev":4928,"_system":4929,"_type":72,"_updatedAt":4932,"author":4933,"category":4937,"date":4941,"description":4942,"image":4951,"name":4985,"orderRank":4986,"reviewer":161,"sections":4987,"seo":161,"slug":5502,"tags":161},"2026-03-31T06:33:26Z","7f6a9ca4-16ce-4257-a281-eae46788255e","wYVuc5B3ng1LhvUVcd33SG",{"base":4930},{"id":4927,"rev":4931},"ReG8cor2CRZQPja7mpcABQ","2026-04-02T13:57:10Z",{"_createdAt":75,"_id":76,"_rev":77,"_type":78,"_updatedAt":79,"image":4934,"linkedin":85,"name":86,"orderRank":40,"position":87,"quote":88,"slug":4936},{"_type":81,"asset":4935},{"_ref":83,"_type":84},{"_type":17,"current":90},{"_createdAt":6,"_id":7,"_rev":8,"_system":4938,"_type":12,"_updatedAt":13,"name":14,"orderRank":15,"slug":4940,"uid":18},{"base":4939},{"id":7,"rev":11},{"_type":17,"current":18},"2026-03-20",[4943],{"_key":4944,"_type":99,"children":4945,"markDefs":4950,"style":107},"cf0b5716ddaa",[4946],{"_key":4947,"_type":103,"marks":4948,"text":4949},"219ca6efada1",[],"Explore 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Databricks Managed Services Into Real Value",[],{"_key":5005,"_type":99,"children":5006,"markDefs":5011,"style":107},"fc2f7f6e3761",[5007],{"_key":5008,"_type":103,"marks":5009,"text":5010},"607b97b654d7",[],"Databricks managed services can feel like a shortcut to fast AI and analytics. You get a lakehouse platform that runs for you, with less platform admin work and quicker ways to test new ideas. For teams under pressure to show real results, that sounds very tempting.",[],{"_key":5013,"_type":99,"children":5014,"markDefs":5019,"style":107},"a0dce9a2cc53",[5015],{"_key":5016,"_type":103,"marks":5017,"text":5018},"9ae4e1ea78f3",[],"But large organisations know there is always a trade. Speed is helpful, yet questions about control, governance, cost and long-term flexibility keep coming back. The smarter question is not “Should we use Databricks managed services?” but “Where do they give us real value, and where do we need more control to protect the business?”",[],{"_key":5021,"_type":99,"children":5022,"markDefs":5027,"style":107},"857cf66c5ea1",[5023],{"_key":5024,"_type":103,"marks":5025,"text":5026},"4a010388744a",[],"At Cosmos Thrace, we see this tension every week. As a Databricks Select Partner, we help design data platforms, governance, and production AI that make the most of managed services without giving up the guardrails that enterprises need.",[],{"_key":5029,"_type":99,"children":5030,"markDefs":5035,"style":182},"4a04fa81d48c",[5031],{"_key":5032,"_type":103,"marks":5033,"text":5034},"501295cf709c",[],"Why Enterprises Are Drawn to Databricks Managed Services",[],{"_key":5037,"_type":99,"children":5038,"markDefs":5043,"style":107},"8f6d7f26bf29",[5039],{"_key":5040,"_type":103,"marks":5041,"text":5042},"758263ba8370",[],"Many data and AI teams are under pressure from leaders and boards. They need working AI use cases, not endless proof-of-concept work. 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The real test is simple: does it actually move the needle on revenue, cost, and risk, or does it just add another line to the cloud bill?",[],{"_key":6172,"_type":99,"children":6173,"markDefs":6178,"style":107},"12a275e046fb",[6174],{"_key":6175,"_type":103,"marks":6176,"text":6177},"3141a08bd741",[],"Right now, AI is speeding up, budgets are tighter, and every pound spent on data and analytics has to prove its worth to finance teams, boards, and frontline leaders. Just saying you \"have Databricks\" does not impress anyone anymore. What matters is whether you are turning that platform into trusted insight and AI that people use every day.",[],{"_key":6180,"_type":99,"children":6181,"markDefs":6186,"style":107},"750a3ce96720",[6182],{"_key":6183,"_type":103,"marks":6184,"text":6185},"258f42470331",[],"This is where your Databricks partner makes or breaks ROI. The right partner turns a lakehouse into a strategic asset. The wrong one leaves you with stalled pilots, rising cloud spend, and AI projects that never leave the lab. We see this often: half-finished proofs of concept, messy governance, and clusters that run all weekend with no clear owner.",[],{"_key":6188,"_type":99,"children":6189,"markDefs":6194,"style":107},"6fb052aee834",[6190],{"_key":6191,"_type":103,"marks":6192,"text":6193},"c1d3c824be9d",[],"At Cosmos Thrace, we work as a Databricks Select Partner focused on measurable business impact, not just technical delivery. 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Then Q1 rolls around, budgets are reviewed after the holidays, and leadership asks a tough question: what did we actually get for that spend?",[],{"_key":6212,"_type":99,"children":6213,"markDefs":6218,"style":107},"6eca36667d19",[6214],{"_key":6215,"_type":103,"marks":6216,"text":6217},"942a165cff78",[],"If the answer is \"some dashboards\" and \"a few AI demos,\" trust starts to slip. Boards and CFOs want clear outcomes, such as:",[],{"_key":6220,"_type":99,"children":6221,"level":230,"listItem":231,"markDefs":6226,"style":107},"029a0d54a31c",[6222],{"_key":6223,"_type":103,"marks":6224,"text":6225},"606708123c1a",[],"Faster time to insight, so decisions are based on fresh data, not last month’s exports",[],{"_key":6228,"_type":99,"children":6229,"level":230,"listItem":231,"markDefs":6234,"style":107},"c7a1606f4305",[6230],{"_key":6231,"_type":103,"marks":6232,"text":6233},"fbf98994b306",[],"Shorter reporting cycles, so teams stop living in manual spreadsheets",[],{"_key":6236,"_type":99,"children":6237,"level":230,"listItem":231,"markDefs":6242,"style":107},"e700c2b7c0a6",[6238],{"_key":6239,"_type":103,"marks":6240,"text":6241},"8e15b7bfad20",[],"AI directly in frontline processes, not sitting in isolated notebooks",[],{"_key":6244,"_type":99,"children":6245,"level":230,"listItem":231,"markDefs":6250,"style":107},"f57c45c2412c",[6246],{"_key":6247,"_type":103,"marks":6248,"text":6249},"a21d4c75e2a9",[],"A lower total cost of ownership over time, not a steady climb in cloud charges",[],{"_key":6252,"_type":99,"children":6253,"markDefs":6258,"style":107},"f620ca1f93e8",[6254],{"_key":6255,"_type":103,"marks":6256,"text":6257},"ef3612c576c0",[],"An experienced Databricks partner helps translate raw platform investment into these outcomes. The difference often comes down to mindset.",[],{"_key":6260,"_type":99,"children":6261,"markDefs":6266,"style":107},"8622e4c3bd83",[6262],{"_key":6263,"_type":103,"marks":6264,"text":6265},"cd0a3c21914f",[],"A tool-centric partner talks about:",[],{"_key":6268,"_type":99,"children":6269,"level":230,"listItem":231,"markDefs":6274,"style":107},"f4658b905458",[6270],{"_key":6271,"_type":103,"marks":6272,"text":6273},"9b2f95ead479",[],"Features and product names",[],{"_key":6276,"_type":99,"children":6277,"level":230,"listItem":231,"markDefs":6282,"style":107},"320fa318bd30",[6278],{"_key":6279,"_type":103,"marks":6280,"text":6281},"9ba0e518addf",[],"Cluster sizes and performance tweaks",[],{"_key":6284,"_type":99,"children":6285,"level":230,"listItem":231,"markDefs":6290,"style":107},"70c7ebe7c787",[6286],{"_key":6287,"_type":103,"marks":6288,"text":6289},"5b58edff9a48",[],"Fancy notebooks and one-off demos",[],{"_key":6292,"_type":99,"children":6293,"markDefs":6298,"style":107},"a1cf80f7c0a8",[6294],{"_key":6295,"_type":103,"marks":6296,"text":6297},"94ff568b0334",[],"An outcome-centric partner starts with:",[],{"_key":6300,"_type":99,"children":6301,"level":230,"listItem":231,"markDefs":6306,"style":107},"a05d6d56cc6c",[6302],{"_key":6303,"_type":103,"marks":6304,"text":6305},"f2206802b183",[],"Clear value hypotheses, like \"cut reporting lag\" or \"improve forecast quality\"",[],{"_key":6308,"_type":99,"children":6309,"level":230,"listItem":231,"markDefs":6314,"style":107},"1108bb463270",[6310],{"_key":6311,"_type":103,"marks":6312,"text":6313},"0cf2cfb89ae4",[],"Agreed KPIs tied to commercial goals",[],{"_key":6316,"_type":99,"children":6317,"level":230,"listItem":231,"markDefs":6322,"style":107},"0d61bd179b99",[6318],{"_key":6319,"_type":103,"marks":6320,"text":6321},"a6fc9d278ad4",[],"A roadmap that lines up with business milestones and funding cycles",[],{"_key":6324,"_type":99,"children":6325,"markDefs":6330,"style":107},"f2f058e50bbd",[6326],{"_key":6327,"_type":103,"marks":6328,"text":6329},"9a2bc3c3a693",[],"Right now, the hype around GenAI is calming and scrutiny is rising. Leaders do not want more pilots that go nowhere. They want production-grade solutions with monitoring, governance, and a path to scale. Your partner’s maturity is what decides whether you can deliver that.",[],{"_key":6332,"_type":99,"children":6333,"markDefs":6338,"style":182},"17dc68642fa8",[6334],{"_key":6335,"_type":103,"marks":6336,"text":6337},"7f21ef8f4f3f",[],"The Traits of a High-Impact Databricks Partner",[],{"_key":6340,"_type":99,"children":6341,"markDefs":6346,"style":107},"5c1372cb82d5",[6342],{"_key":6343,"_type":103,"marks":6344,"text":6345},"dd1bacb52c10",[],"So what should you actually look for when you choose a Databricks partner? A strong partner is more than a team of good engineers.",[],{"_key":6348,"_type":99,"children":6349,"markDefs":6354,"style":107},"37d5467e7a17",[6350],{"_key":6351,"_type":103,"marks":6352,"text":6353},"075489f01b62",[],"First, there is strategic alignment, not just configuration. A serious partner will:",[],{"_key":6356,"_type":99,"children":6357,"level":230,"listItem":231,"markDefs":6362,"style":107},"d30b3bb9f3e0",[6358],{"_key":6359,"_type":103,"marks":6360,"text":6361},"594aee5f687f",[],"Challenge your use cases and ask \"why\" more than once",[],{"_key":6364,"_type":99,"children":6365,"level":230,"listItem":231,"markDefs":6370,"style":107},"123fef8167ee",[6366],{"_key":6367,"_type":103,"marks":6368,"text":6369},"93cbf18b1cdb",[],"Link each initiative to revenue growth, margin, or risk reduction",[],{"_key":6372,"_type":99,"children":6373,"level":230,"listItem":231,"markDefs":6378,"style":107},"c365b5502374",[6374],{"_key":6375,"_type":103,"marks":6376,"text":6377},"48fd21bc650e",[],"Help you pick quick wins that prove ROI early, not in a distant future",[],{"_key":6380,"_type":99,"children":6381,"markDefs":6386,"style":107},"4c087fcd68c8",[6382],{"_key":6383,"_type":103,"marks":6384,"text":6385},"906da808c372",[],"Second, they bring deep Databricks and lakehouse expertise. 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Your Lakehouse Vision Hits a Wall",[],{"_key":6924,"_type":99,"children":6925,"markDefs":6930,"style":107},"7bb6a36baf14",[6926],{"_key":6927,"_type":103,"marks":6928,"text":6929},"7bc86980e1c4",[],"Enterprise lakehouse implementation often starts with big energy. New platform, clean architecture, clear vision for data and AI. Then months pass, things get messy, and the shine fades. Workloads grow, costs creep up, and everyone keeps asking, where is the real value?",[],{"_key":6932,"_type":99,"children":6933,"markDefs":6938,"style":107},"891788018532",[6934],{"_key":6935,"_type":103,"marks":6936,"text":6937},"4910b767f850",[],"This is where many teams find themselves. The Databricks-based lakehouse is standing, but progress feels slow and fragile. It is hard to get changes safely into production, AI work stays stuck in notebooks, and leaders start to worry they backed the wrong approach. In this article, we will talk about why momentum stalls and what we can actually do to restart it, without burning out our teams.",[],{"_key":6940,"_type":99,"children":6941,"markDefs":6946,"style":107},"504cdcbab8b7",[6942],{"_key":6943,"_type":103,"marks":6944,"text":6945},"dc401ba9d750",[],"We see these problems often, from our base in Europe, where cloud costs, data regulations, and pressure around GenAI are all rising at the same time. The good news is that a stalled lakehouse is not a failed lakehouse. With the right focus, it can still become the foundation for serious data and AI value.",[],{"_key":6948,"_type":99,"children":6949,"markDefs":6954,"style":182},"f112bfaf4570",[6950],{"_key":6951,"_type":103,"marks":6952,"text":6953},"64bf7ceb64cb",[],"Recognising When Your Lakehouse Has Stalled",[],{"_key":6956,"_type":99,"children":6957,"markDefs":6962,"style":107},"2a07d5498a1a",[6958],{"_key":6959,"_type":103,"marks":6960,"text":6961},"18ffd264e112",[],"The first step is to be honest about what is really happening. A lakehouse does not stop in one day; it slows down in small steps that are easy to ignore.",[],{"_key":6964,"_type":99,"children":6965,"markDefs":6970,"style":107},"42b6486aef57",[6966],{"_key":6967,"_type":103,"marks":6968,"text":6969},"d1065156ca03",[],"Common operational red flags include:",[],{"_key":6972,"_type":99,"children":6973,"level":230,"listItem":231,"markDefs":6978,"style":107},"0645a3c18389",[6974],{"_key":6975,"_type":103,"marks":6976,"text":6977},"a254c6849cfa",[],"Pipelines that fail overnight, then get fixed by hand again and again",[],{"_key":6980,"_type":99,"children":6981,"level":230,"listItem":231,"markDefs":6986,"style":107},"d480d67f8345",[6982],{"_key":6983,"_type":103,"marks":6984,"text":6985},"6b9b0862492b",[],"Jobs that run far longer than they should, without anyone knowing why",[],{"_key":6988,"_type":99,"children":6989,"level":230,"listItem":231,"markDefs":6994,"style":107},"e739fbecabe1",[6990],{"_key":6991,"_type":103,"marks":6992,"text":6993},"d3aeb36d6963",[],"Cloud spend rising faster than the value you can point to",[],{"_key":6996,"_type":99,"children":6997,"level":230,"listItem":231,"markDefs":7002,"style":107},"3f0956a3924c",[6998],{"_key":6999,"_type":103,"marks":7000,"text":7001},"897ccbaffce1",[],"Teams quietly keeping old warehouses alive \"just in case\"",[],{"_key":7004,"_type":99,"children":7005,"markDefs":7010,"style":107},"763e8dd03880",[7006],{"_key":7007,"_type":103,"marks":7008,"text":7009},"c54d8dcef47b",[],"On the people side, the signs are just as clear:",[],{"_key":7012,"_type":99,"children":7013,"level":230,"listItem":231,"markDefs":7018,"style":107},"3031810cf00e",[7014],{"_key":7015,"_type":103,"marks":7016,"text":7017},"1b017a7ccdf2",[],"Data engineers spend most of their time firefighting, not improving the platform",[],{"_key":7020,"_type":99,"children":7021,"level":230,"listItem":231,"markDefs":7026,"style":107},"96927fc32c5c",[7022],{"_key":7023,"_type":103,"marks":7024,"text":7025},"f368b12fa990",[],"Analysts export data to spreadsheets because they do not trust what they see in the lakehouse",[],{"_key":7028,"_type":99,"children":7029,"level":230,"listItem":231,"markDefs":7034,"style":107},"0f4cfd0ffb34",[7030],{"_key":7031,"_type":103,"marks":7032,"text":7033},"6861670bbbb7",[],"Data scientists wait days or weeks for access to well-governed data, or they build their own copies",[],{"_key":7036,"_type":99,"children":7037,"markDefs":7042,"style":107},"cecf84506ee3",[7038],{"_key":7039,"_type":103,"marks":7040,"text":7041},"a67178f8b0d2",[],"Then there are the strategic warning signs. New data products keep slipping from the roadmap. AI work stays as proof-of-concept instead of powering real services. Steering groups start asking harder questions about the lakehouse vision and whether it will ever land. When this happens, we are not just dealing with a technical issue; we are dealing with confidence.",[],{"_key":7044,"_type":99,"children":7045,"markDefs":7050,"style":182},"eac2082435e4",[7046],{"_key":7047,"_type":103,"marks":7048,"text":7049},"5dbf97b769e2",[],"Root Causes Behind Stalled Lakehouse Programmes",[],{"_key":7052,"_type":99,"children":7053,"markDefs":7058,"style":107},"949b7fd46c77",[7054],{"_key":7055,"_type":103,"marks":7056,"text":7057},"f0682549a8f0",[],"A lakehouse rarely stalls due to one single problem. It is usually a mix of weak foundations, gaps in the operating model, and a fuzzy link back to business goals.",[],{"_key":7060,"_type":99,"children":7061,"markDefs":7066,"style":107},"46bbdcb25c2c",[7062],{"_key":7063,"_type":103,"marks":7064,"text":7065},"5bf197d7c153",[],"On the technical side, we often see:",[],{"_key":7068,"_type":99,"children":7069,"level":230,"listItem":231,"markDefs":7074,"style":107},"92221b2cd88b",[7070],{"_key":7071,"_type":103,"marks":7072,"text":7073},"34961505aac1",[],"No clear data governance model across the lakehouse",[],{"_key":7076,"_type":99,"children":7077,"level":230,"listItem":231,"markDefs":7082,"style":107},"0df334b0b3f8",[7078],{"_key":7079,"_type":103,"marks":7080,"text":7081},"c6b9aed6b2a8",[],"Inconsistent practices for Delta Lake, so each team does things differently",[],{"_key":7084,"_type":99,"children":7085,"level":230,"listItem":231,"markDefs":7090,"style":107},"575ad08e0c81",[7086],{"_key":7087,"_type":103,"marks":7088,"text":7089},"591168645454",[],"Little or no observability for pipelines and queries",[],{"_key":7092,"_type":99,"children":7093,"level":230,"listItem":231,"markDefs":7098,"style":107},"f21273d05d27",[7094],{"_key":7095,"_type":103,"marks":7096,"text":7097},"f9578f746eba",[],"No shared way of managing performance or keeping costs under control",[],{"_key":7100,"_type":99,"children":7101,"markDefs":7106,"style":107},"abf82be61140",[7102],{"_key":7103,"_type":103,"marks":7104,"text":7105},"1b442b841918",[],"Then there is the operating model. Who owns what? Many programmes start with unclear lines between:",[],{"_key":7108,"_type":99,"children":7109,"level":230,"listItem":231,"markDefs":7114,"style":107},"909b9bc3b5e1",[7110],{"_key":7111,"_type":103,"marks":7112,"text":7113},"4c726aff665d",[],"Platform teams, who run Databricks and the shared services",[],{"_key":7116,"_type":99,"children":7117,"level":230,"listItem":231,"markDefs":7122,"style":107},"a112d0fb0766",[7118],{"_key":7119,"_type":103,"marks":7120,"text":7121},"f2be6205d1e4",[],"Domain or data teams, who own specific data sets and models",[],{"_key":7124,"_type":99,"children":7125,"level":230,"listItem":231,"markDefs":7130,"style":107},"ddb42380bfdc",[7126],{"_key":7127,"_type":103,"marks":7128,"text":7129},"b7a9a9438bf6",[],"Business teams, who rely on data-driven decisions and AI outcomes",[],{"_key":7132,"_type":99,"children":7133,"markDefs":7138,"style":107},"e63b77b8b0c8",[7134],{"_key":7135,"_type":103,"marks":7136,"text":7137},"209cf1a6a095",[],"Without clear ownership, every pattern becomes a one-off. People reinvent ingestion, quality checks, and security each time. There is also a big training gap when teams are new to Databricks and the lakehouse way of working.",[],{"_key":7140,"_type":99,"children":7141,"markDefs":7146,"style":107},"f184b876aa6e",[7142],{"_key":7143,"_type":103,"marks":7144,"text":7145},"bd4219dbe32f",[],"Finally, there is strategy. Some organisations go for a big bang, trying to move everything at once. Others see the lakehouse as an IT upgrade, not a shared business platform. Change management gets pushed aside, so users never fully move across. At that point, even good technical work struggles to show value.",[],{"_key":7148,"_type":99,"children":7149,"markDefs":7154,"style":182},"44f420be98e5",[7150],{"_key":7151,"_type":103,"marks":7152,"text":7153},"e6dc6a923c58",[],"Getting Enterprise Lakehouse Implementations Back on Track",[],{"_key":7156,"_type":99,"children":7157,"markDefs":7162,"style":107},"05227f56468e",[7158],{"_key":7159,"_type":103,"marks":7160,"text":7161},"18f9a8db7657",[],"To restart a stalled programme, we need to shrink the problem and make it real. That starts with outcomes, not technology.",[],{"_key":7164,"_type":99,"children":7165,"markDefs":7170,"style":107},"658ac4d7069a",[7166],{"_key":7167,"_type":103,"marks":7168,"text":7169},"8750644b8172",[],"Pick a small set of use cases that matter and can show value quickly. Typical examples include:",[],{"_key":7172,"_type":99,"children":7173,"level":230,"listItem":231,"markDefs":7178,"style":107},"57cf06cae1cb",[7174],{"_key":7175,"_type":103,"marks":7176,"text":7177},"02c55d3f3508",[],"A clear, trusted customer 360 view for marketing and service teams",[],{"_key":7180,"_type":99,"children":7181,"level":230,"listItem":231,"markDefs":7186,"style":107},"cb72b4366aea",[7182],{"_key":7183,"_type":103,"marks":7184,"text":7185},"75420ba20508",[],"Faster, more transparent risk or regulatory reporting",[],{"_key":7188,"_type":99,"children":7189,"level":230,"listItem":231,"markDefs":7194,"style":107},"2a2ace3c261a",[7190],{"_key":7191,"_type":103,"marks":7192,"text":7193},"c627b810f34e",[],"Better demand forecasting for supply chain or operations",[],{"_key":7196,"_type":99,"children":7197,"markDefs":7202,"style":107},"755f331fd378",[7198],{"_key":7199,"_type":103,"marks":7200,"text":7201},"c0108a097767",[],"These should be scoped so that we can show visible results within one quarter, not in some far-off future state. Every technical change then lines up behind these outcomes.",[],{"_key":7204,"_type":99,"children":7205,"markDefs":7210,"style":107},"2f183dc06a45",[7206],{"_key":7207,"_type":103,"marks":7208,"text":7209},"d057c3938581",[],"Next, we stabilise the platform. That often means:",[],{"_key":7212,"_type":99,"children":7213,"level":230,"listItem":231,"markDefs":7218,"style":107},"7b8c445375e3",[7214],{"_key":7215,"_type":103,"marks":7216,"text":7217},"92476686b837",[],"Standardising ingestion patterns, for both batch and streaming",[],{"_key":7220,"_type":99,"children":7221,"level":230,"listItem":231,"markDefs":7226,"style":107},"e7753248609b",[7222],{"_key":7223,"_type":103,"marks":7224,"text":7225},"2aec1f8cad25",[],"Adopting clear modelling layers for raw, cleaned, and curated data",[],{"_key":7228,"_type":99,"children":7229,"level":230,"listItem":231,"markDefs":7234,"style":107},"e81558de4e88",[7230],{"_key":7231,"_type":103,"marks":7232,"text":7233},"eb285a68d87b",[],"Introducing monitoring, alerts, and CI/CD for data and ML workloads",[],{"_key":7236,"_type":99,"children":7237,"level":230,"listItem":231,"markDefs":7242,"style":107},"106ceba56987",[7238],{"_key":7239,"_type":103,"marks":7240,"text":7241},"4e2a862edd32",[],"Fixing the worst data quality issues that block users day to day",[],{"_key":7244,"_type":99,"children":7245,"markDefs":7250,"style":107},"d67712c747ba",[7246],{"_key":7247,"_type":103,"marks":7248,"text":7249},"44f99b778978",[],"Governance needs a refresh too. Instead of trying to perfect everything, we give people just enough structure to trust the lakehouse:",[],{"_key":7252,"_type":99,"children":7253,"level":230,"listItem":231,"markDefs":7258,"style":107},"bef80ecebb4f",[7254],{"_key":7255,"_type":103,"marks":7256,"text":7257},"56a38dc3edf9",[],"Simple, clear access controls that match real business roles",[],{"_key":7260,"_type":99,"children":7261,"level":230,"listItem":231,"markDefs":7266,"style":107},"bfc7b21ecec7",[7262],{"_key":7263,"_type":103,"marks":7264,"text":7265},"4ef42cc1ac66",[],"Lineage so teams can see where data came from and how it was changed",[],{"_key":7268,"_type":99,"children":7269,"level":230,"listItem":231,"markDefs":7274,"style":107},"341fb2330daa",[7270],{"_key":7271,"_type":103,"marks":7272,"text":7273},"4b0fa287df75",[],"A catalogue that business users can search and actually understand",[],{"_key":7276,"_type":99,"children":7277,"markDefs":7282,"style":107},"d1c078b2b1ca",[7278],{"_key":7279,"_type":103,"marks":7280,"text":7281},"c244bc8add4d",[],"With these basics in place, confidence starts to return, and future work becomes easier, not harder.",[],{"_key":7284,"_type":99,"children":7285,"markDefs":7290,"style":182},"ec4d1b67f3b8",[7286],{"_key":7287,"_type":103,"marks":7288,"text":7289},"c554c6e2458d",[],"Turning Data and AI From Experiments Into Products",[],{"_key":7292,"_type":99,"children":7293,"markDefs":7298,"style":107},"eb6a82fac966",[7294],{"_key":7295,"_type":103,"marks":7296,"text":7297},"e606715504f1",[],"A big mindset shift is to treat data and AI as products, not experiments or projects. That means each important data set, report, feature store, or model has:",[],{"_key":7300,"_type":99,"children":7301,"level":230,"listItem":231,"markDefs":7306,"style":107},"cc07e195a5fa",[7302],{"_key":7303,"_type":103,"marks":7304,"text":7305},"a92dab8fe84b",[],"A clear owner",[],{"_key":7308,"_type":99,"children":7309,"level":230,"listItem":231,"markDefs":7314,"style":107},"92618dacd0aa",[7310],{"_key":7311,"_type":103,"marks":7312,"text":7313},"c33c92491390",[],"Defined users and expected outcomes",[],{"_key":7316,"_type":99,"children":7317,"level":230,"listItem":231,"markDefs":7322,"style":107},"662d492927c5",[7318],{"_key":7319,"_type":103,"marks":7320,"text":7321},"cad486dd1572",[],"Service levels, such as freshness or accuracy",[],{"_key":7324,"_type":99,"children":7325,"level":230,"listItem":231,"markDefs":7330,"style":107},"2eb6a973ad3c",[7326],{"_key":7327,"_type":103,"marks":7328,"text":7329},"d2d38458edc0",[],"A roadmap and a loop for user feedback",[],{"_key":7332,"_type":99,"children":7333,"markDefs":7338,"style":107},"54975a588543",[7334],{"_key":7335,"_type":103,"marks":7336,"text":7337},"8355247f2631",[],"This product thinking pushes us to care about reliability, usability, and long-term value, not just first delivery.",[],{"_key":7340,"_type":99,"children":7341,"markDefs":7346,"style":107},"7a395aeeff85",[7342],{"_key":7343,"_type":103,"marks":7344,"text":7345},"0b0613422566",[],"On the AI side, we move from one-off notebooks to clean, repeatable workflows. That usually includes:",[],{"_key":7348,"_type":99,"children":7349,"level":230,"listItem":231,"markDefs":7354,"style":107},"e04a0e137bd4",[7350],{"_key":7351,"_type":103,"marks":7352,"text":7353},"302352c717ae",[],"Feature stores that are shared, documented, and governed",[],{"_key":7356,"_type":99,"children":7357,"level":230,"listItem":231,"markDefs":7362,"style":107},"c5989533f97b",[7358],{"_key":7359,"_type":103,"marks":7360,"text":7361},"5de5d679d8d1",[],"Standard patterns for training, testing, and deploying models",[],{"_key":7364,"_type":99,"children":7365,"level":230,"listItem":231,"markDefs":7370,"style":107},"59387a78d4ce",[7366],{"_key":7367,"_type":103,"marks":7368,"text":7369},"ec58d798bf96",[],"Reproducible GenAI workflows that respect security and compliance",[],{"_key":7372,"_type":99,"children":7373,"markDefs":7378,"style":107},"8b6538028020",[7374],{"_key":7375,"_type":103,"marks":7376,"text":7377},"14a1812ddf1d",[],"Databricks is strong here because it brings data, streaming, and ML together in one place, with integrated governance. Used well, that means fewer handoffs, fewer copies of data, and a smoother path from idea to production.",[],{"_key":7380,"_type":99,"children":7381,"markDefs":7386,"style":182},"fdbe82933eb4",[7382],{"_key":7383,"_type":103,"marks":7384,"text":7385},"70315e17dd89",[],"Partnering to Accelerate Your Lakehouse Momentum",[],{"_key":7388,"_type":99,"children":7389,"markDefs":7394,"style":107},"264f97dc0866",[7390],{"_key":7391,"_type":103,"marks":7392,"text":7393},"86ed041e7a42",[],"There comes a point where internal teams are too deep in the day-to-day to reset things alone. If your programme is stuck in long-standing proof-of-concept loops, if the same issues keep coming back, or if stakeholders are losing patience, that is usually the time to bring in fresh eyes.",[],{"_key":7396,"_type":99,"children":7397,"markDefs":7402,"style":107},"b469797ecf2f",[7398],{"_key":7399,"_type":103,"marks":7400,"text":7401},"47a1240d453c",[],"A specialist Databricks partner can help by:",[],{"_key":7404,"_type":99,"children":7405,"level":230,"listItem":231,"markDefs":7410,"style":107},"0d0636b5eef7",[7406],{"_key":7407,"_type":103,"marks":7408,"text":7409},"544f1b923e19",[],"Reviewing your current architecture and finding quick wins",[],{"_key":7412,"_type":99,"children":7413,"level":230,"listItem":231,"markDefs":7418,"style":107},"377972bd188c",[7414],{"_key":7415,"_type":103,"marks":7416,"text":7417},"4cab784f9720",[],"Tuning cost and performance without breaking what already works",[],{"_key":7420,"_type":99,"children":7421,"level":230,"listItem":231,"markDefs":7426,"style":107},"9b32aa3f44cd",[7422],{"_key":7423,"_type":103,"marks":7424,"text":7425},"440ab195e96c",[],"Defining clear patterns and operating models for teams to follow",[],{"_key":7428,"_type":99,"children":7429,"level":230,"listItem":231,"markDefs":7434,"style":107},"c212acfe064b",[7430],{"_key":7431,"_type":103,"marks":7432,"text":7433},"04dea5859cdf",[],"Delivering a focused, production-grade slice of data and AI that rebuilds trust",[],{"_key":7436,"_type":99,"children":7437,"markDefs":7442,"style":107},"1babb9c5b44f",[7438],{"_key":7439,"_type":103,"marks":7440,"text":7441},"4729fb6f8915",[],"At Cosmos Thrace, as a Databricks Select Partner, our work is focused on modernising data platforms and turning lakehouse ideas into production reality. We see how weather, business cycles, and planning seasons all affect when leaders can make changes, and we try to align with that rhythm. When organisations commit to a short, sharp recovery phase with clear outcomes, the lakehouse stops feeling like an endless project and starts acting like the business platform it was meant to be.",[],{"_key":7444,"_type":99,"children":7445,"markDefs":7449,"style":182},"162a0898b098",[7446],{"_key":7447,"_type":103,"marks":7448,"text":767},"8f795407268f",[],[],{"_key":7451,"_type":99,"children":7452,"markDefs":7473,"style":107},"4dcd845bdb8d",[7453,7457,7461,7465,7469],{"_key":7454,"_type":103,"marks":7455,"text":7456},"0087ae6c9058",[],"If you are ready to move from theory to delivery, our specialists can guide your ",{"_key":7458,"_type":103,"marks":7459,"text":6065},"445f84123766",[7460],"93dbf89dea7e",{"_key":7462,"_type":103,"marks":7463,"text":7464},"5cf6daf67c6a",[]," from initial design through to production. At Cosmos Thrace, we align data architecture with your business priorities so you see measurable outcomes, not just new technology. To discuss your requirements and timelines, simply ",{"_key":7466,"_type":103,"marks":7467,"text":789},"e4d0dd91d1b4",[7468],"3db101e75778",{"_key":7470,"_type":103,"marks":7471,"text":7472},"b8c38d595321",[]," and we will help you define the next steps with clarity and confidence.",[7474,7475],{"_key":7460,"_type":173,"href":796},{"_key":7468,"_type":173,"href":798},{"_type":17,"current":7477},"when-enterprise-lakehouse-implementation-stalls",{"_createdAt":7479,"_id":7480,"_rev":7481,"_system":7482,"_type":72,"_updatedAt":7485,"author":7486,"category":7490,"date":7494,"description":7495,"image":7504,"name":7537,"orderRank":7538,"reviewer":161,"sections":7539,"seo":161,"slug":7856,"tags":161},"2026-03-31T06:25:57Z","a8c71e46-33d1-411f-a10f-e55e89d7c6fb","HDlNiVeMvqybGjkmBvfNvW",{"base":7483},{"id":7480,"rev":7484},"wYVuc5B3ng1LhvUVccWI6G","2026-04-03T10:47:47Z",{"_createdAt":75,"_id":76,"_rev":77,"_type":78,"_updatedAt":79,"image":7487,"linkedin":85,"name":86,"orderRank":40,"position":87,"quote":88,"slug":7489},{"_type":81,"asset":7488},{"_ref":83,"_type":84},{"_type":17,"current":90},{"_createdAt":6,"_id":7,"_rev":8,"_system":7491,"_type":12,"_updatedAt":13,"name":14,"orderRank":15,"slug":7493,"uid":18},{"base":7492},{"id":7,"rev":11},{"_type":17,"current":18},"2026-03-06",[7496],{"_key":7497,"_type":99,"children":7498,"markDefs":7503,"style":107},"4c9ff05bf5fe",[7499],{"_key":7500,"_type":103,"marks":7501,"text":7502},"cf682dca48b1",[],"Explore 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Databricks Migration: Strategies for a Smooth Move","0|1000zc:",[7540],{"_createdAt":7541,"_id":7542,"_key":7543,"_ref":7542,"_rev":7544,"_system":7545,"_type":168,"_updatedAt":7548,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":7549,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:26Z","1J047RIbsVKaGOG92ISsj","43a01fd03614","M1MfPf0YfIiifMUjXOydwu",{"base":7546},{"id":7542,"rev":7547},"M1MfPf0YfIiifMUjXOx9oa","2026-03-31T06:28:12Z",[7550,7558,7566,7574,7582,7590,7598,7606,7614,7622,7630,7638,7646,7654,7662,7670,7678,7686,7694,7702,7710,7718,7726,7734,7742,7750,7758,7766,7774,7782,7790,7798,7806,7814,7822,7830],{"_key":7551,"_type":99,"children":7552,"markDefs":7557,"style":182},"c1589f0aeeb4",[7553],{"_key":7554,"_type":103,"marks":7555,"text":7556},"eb57487b3b4f",[],"Turning Databricks Migration Into a Competitive Advantage",[],{"_key":7559,"_type":99,"children":7560,"markDefs":7565,"style":107},"a8d281aec7c2",[7561],{"_key":7562,"_type":103,"marks":7563,"text":7564},"1bee4f22fbba",[],"Databricks migration is not just another platform swap; it is a chance to reset how your organisation thinks about data, analytics, and AI. When you move from legacy warehouses or first-generation cloud data platforms into Databricks, you are opening the door to faster experimentation, simpler data access and more reliable machine learning at scale.",[],{"_key":7567,"_type":99,"children":7568,"markDefs":7573,"style":107},"7aecbbec2e23",[7569],{"_key":7570,"_type":103,"marks":7571,"text":7572},"f4cd5cd271a2",[],"At Cosmos Thrace, we see organisations across Europe wrestling with similar challenges. They are held back by brittle ETL jobs, siloed warehouses, escalating costs and analytical teams spending more time fixing data than using it. Migration can feel risky, especially when revenue reporting, regulatory submissions or critical operational dashboards depend on systems that have grown over many years. This article shares practical Databricks migration strategies we have refined in consulting engagements, so you can reduce risk, avoid common pitfalls and start realising value earlier in the programme.",[],{"_key":7575,"_type":99,"children":7576,"markDefs":7581,"style":182},"3bf2257f697c",[7577],{"_key":7578,"_type":103,"marks":7579,"text":7580},"6d5d0a8a90cf",[],"Clarifying Why You Are Migrating to Databricks",[],{"_key":7583,"_type":99,"children":7584,"markDefs":7589,"style":107},"88fbdd4fe86a",[7585],{"_key":7586,"_type":103,"marks":7587,"text":7588},"5c9f77d63564",[],"A successful Databricks migration starts with a very clear answer to a basic question: why are we doing this at all? Without shared outcomes, migrations drift and tooling debates swamp the bigger picture. We encourage teams to frame targets in business terms, such as accelerating time to insight, reducing total cost of ownership, enabling AI use cases or meeting stricter compliance expectations.",[],{"_key":7591,"_type":99,"children":7592,"markDefs":7597,"style":107},"e7eca5f232eb",[7593],{"_key":7594,"_type":103,"marks":7595,"text":7596},"00201f4d0a20",[],"Once those outcomes are defined, you can connect them to specific Databricks capabilities. For example, if your challenge is duplicated logic across multiple warehouses and lakes, the Lakehouse architecture and Delta Lake help you converge analytics on a single, governed data layer. If you struggle with scattered permissions, Unity Catalog provides centralised governance. If your batch pipelines are fragile, Delta Live Tables supports more reliable data engineering with built-in expectations and monitoring.",[],{"_key":7599,"_type":99,"children":7600,"markDefs":7605,"style":107},"e2f12c33ba99",[7601],{"_key":7602,"_type":103,"marks":7603,"text":7604},"29e2760e7592",[],"This is also the moment to secure active executive sponsorship. Migration means changing how teams work, how projects are funded and how success is measured. When business and IT leaders share a simple migration narrative, such as \"we are moving to Databricks to speed up decisions and prepare for AI safely\", it becomes easier to align priorities and defend the investment when trade-offs appear.",[],{"_key":7607,"_type":99,"children":7608,"markDefs":7613,"style":182},"a77359fc82a0",[7609],{"_key":7610,"_type":103,"marks":7611,"text":7612},"3c48a870250e",[],"Assessing Your Current Data Landscape with Precision",[],{"_key":7615,"_type":99,"children":7616,"markDefs":7621,"style":107},"953069531624",[7617],{"_key":7618,"_type":103,"marks":7619,"text":7620},"e554a05ebccd",[],"Before touching any production workload, invest time in understanding what you already have. A thorough assessment covers data sources, integration tools, warehouses, existing data lakes, BI platforms and any current machine learning workloads. The aim is to get a realistic view of what is in scope, how it is connected and where the most fragile points are.",[],{"_key":7623,"_type":99,"children":7624,"markDefs":7629,"style":107},"2d2d5a26a9c6",[7625],{"_key":7626,"_type":103,"marks":7627,"text":7628},"728e95238981",[],"We find it helpful to classify workloads so migration can be sequenced logically. For each pipeline, report or model, you might ask:",[],{"_key":7631,"_type":99,"children":7632,"level":230,"listItem":231,"markDefs":7637,"style":107},"f4126e2b2607",[7633],{"_key":7634,"_type":103,"marks":7635,"text":7636},"006d2fa3fdd6",[],"How critical is this for day-to-day operations or regulatory reporting?",[],{"_key":7639,"_type":99,"children":7640,"level":230,"listItem":231,"markDefs":7645,"style":107},"49a1acad9030",[7641],{"_key":7642,"_type":103,"marks":7643,"text":7644},"23f8f5fd1f74",[],"How complex is the logic and how well is it documented?",[],{"_key":7647,"_type":99,"children":7648,"level":230,"listItem":231,"markDefs":7653,"style":107},"c2502673409b",[7649],{"_key":7650,"_type":103,"marks":7651,"text":7652},"8e3574387908",[],"What are the current performance issues or service level expectations?",[],{"_key":7655,"_type":99,"children":7656,"level":230,"listItem":231,"markDefs":7661,"style":107},"9b641023c0e2",[7657],{"_key":7658,"_type":103,"marks":7659,"text":7660},"3bcc79cb2f16",[],"Does this touch sensitive, personal or regulated data?",[],{"_key":7663,"_type":99,"children":7664,"markDefs":7669,"style":107},"ef0ccf5eb282",[7665],{"_key":7666,"_type":103,"marks":7667,"text":7668},"240115009ce5",[],"This classification guides which workloads become early pilots and which are moved later with extra safeguards. Alongside this, you should run platform and security assessments. Check identity and access management, data protection controls and how ready your current cloud environment is for Databricks. For organisations still moving to Azure, AWS or Google Cloud, this is the time to coordinate cloud foundation work with the Databricks plan so you do not discover network or governance gaps mid migration.",[],{"_key":7671,"_type":99,"children":7672,"markDefs":7677,"style":182},"e60c8f0e74c2",[7673],{"_key":7674,"_type":103,"marks":7675,"text":7676},"7a6743d0ff9b",[],"Designing a Future-Proof Databricks Architecture",[],{"_key":7679,"_type":99,"children":7680,"markDefs":7685,"style":107},"8c5334052652",[7681],{"_key":7682,"_type":103,"marks":7683,"text":7684},"ad40b841d93d",[],"With a clear view of your current state, you can design a Databricks architecture that will serve you for years, not just for the migration window. Selecting the right cloud provider is usually tied to your wider IT strategy, existing contracts and data residency needs. From there, you will need decisions on account structure and workspace strategy, for example whether to separate development, test and production workspaces, or organise workspaces by business domain or geography.",[],{"_key":7687,"_type":99,"children":7688,"markDefs":7693,"style":107},"6a70dcc6ff41",[7689],{"_key":7690,"_type":103,"marks":7691,"text":7692},"ca1e842d269f",[],"At the data layer, we typically recommend a Lakehouse architecture based on Delta Lake and Unity Catalog. Medallion patterns, with bronze, silver and gold layers, help keep ingestion, cleansing and serving concerns separate. This approach supports data quality, reuse and governance, while making it easier for analysts and data scientists to understand where to work. Unity Catalog sits across this to manage permissions, lineage and auditing in a single place.",[],{"_key":7695,"_type":99,"children":7696,"markDefs":7701,"style":107},"4f079dc13242",[7697],{"_key":7698,"_type":103,"marks":7699,"text":7700},"4e0061cff5f1",[],"Performance, cost and productivity should be designed in from the start, not added as an afterthought. That can include standardised cluster policies to control spend, shared job orchestration patterns, common libraries and templates for ETL, and monitoring that combines Databricks metrics with your existing observability tools. A small investment in reusable patterns pays off when multiple teams begin building on Databricks in parallel.",[],{"_key":7703,"_type":99,"children":7704,"markDefs":7709,"style":182},"beb44a8d5ff7",[7705],{"_key":7706,"_type":103,"marks":7707,"text":7708},"12720c7449e0",[],"Planning and Executing Migration in Manageable Phases",[],{"_key":7711,"_type":99,"children":7712,"markDefs":7717,"style":107},"4d7bb0fb91a1",[7713],{"_key":7714,"_type":103,"marks":7715,"text":7716},"149896fcceb3",[],"A big-bang migration of every pipeline and report is rarely the right answer. Instead, take a phased approach that lets you learn, adapt and build confidence. Many organisations start with a proof of concept focused on a contained use case, then move to a pilot domain that exercises more of the platform, such as a finance or supply chain area, before expanding to wider enterprise adoption.",[],{"_key":7719,"_type":99,"children":7720,"markDefs":7725,"style":107},"463d653c1d90",[7721],{"_key":7722,"_type":103,"marks":7723,"text":7724},"c4922d2b5b74",[],"Migration activities usually span ETL and ELT pipelines, SQL workloads, BI dashboards and machine learning models. For pipelines, you might re-implement in Databricks using Delta Live Tables or standard jobs, rather than attempting like-for-like code translation. For SQL workloads and BI tools, ensure you have a clear strategy for data access patterns so reports can switch over without surprises. Machine learning models often benefit from refactoring to take advantage of Databricks notebooks and ML tooling.",[],{"_key":7727,"_type":99,"children":7728,"markDefs":7733,"style":107},"0008a268e850",[7729],{"_key":7730,"_type":103,"marks":7731,"text":7732},"eb9c76206452",[],"Cutover planning is where risk is actively managed. We recommend defined periods of dual running, where old and new platforms operate together. During this time, teams can perform regression testing, reconcile numbers, and benchmark performance. A structured communication plan keeps business users informed about what is changing, when, and how to flag issues quickly if something does not look right.",[],{"_key":7735,"_type":99,"children":7736,"markDefs":7741,"style":182},"85b5bc72aecb",[7737],{"_key":7738,"_type":103,"marks":7739,"text":7740},"6870467a1c6b",[],"Modernising Governance, Security and Operating Models",[],{"_key":7743,"_type":99,"children":7744,"markDefs":7749,"style":107},"0591a2d0fb1a",[7745],{"_key":7746,"_type":103,"marks":7747,"text":7748},"8c9b60c7b3a4",[],"Databricks migration is a natural moment to refresh how you govern and secure data. Unity Catalog enables central access control, data discovery, lineage and audit capabilities, which is particularly important for organisations working under European regulations and data protection expectations. Rather than lifting old complex permission models into Databricks, many teams choose to simplify and standardise during migration.",[],{"_key":7751,"_type":99,"children":7752,"markDefs":7757,"style":107},"fe4b20699cb1",[7753],{"_key":7754,"_type":103,"marks":7755,"text":7756},"49d60569792e",[],"On the security side, pay close attention to network design, encryption at rest and in transit, and secrets management for keys and credentials. Databricks should tie into your existing enterprise identity provider so that access is based on familiar roles and groups. These design choices not only protect sensitive data, they also make compliance reviews and audits far easier over time.",[],{"_key":7759,"_type":99,"children":7760,"markDefs":7765,"style":107},"8e6b13d09357",[7761],{"_key":7762,"_type":103,"marks":7763,"text":7764},"0b3b8ab5fe6f",[],"Operating models often need just as much attention as technical architecture. Databricks works best when DevOps and DataOps practices are in place: version control for notebooks and jobs, automated testing, continuous integration and repeatable deployment. You will also want clarity on who owns the platform, how requests are prioritised and how communities of practice, training and documentation will help teams become confident users instead of relying solely on central specialists.",[],{"_key":7767,"_type":99,"children":7768,"markDefs":7773,"style":182},"9ca171eedb89",[7769],{"_key":7770,"_type":103,"marks":7771,"text":7772},"7dbb09847c8a",[],"Accelerating AI and Analytics Value After Migration",[],{"_key":7775,"_type":99,"children":7776,"markDefs":7781,"style":107},"f0d85bb99780",[7777],{"_key":7778,"_type":103,"marks":7779,"text":7780},"5a4ac39f1060",[],"Once your core data workloads are stable on Databricks, the real opportunity begins. A unified Lakehouse creates a single, high-quality foundation for analytics, classical machine learning and newer generative AI use cases that were hard or impossible on fragmented legacy stacks. Data scientists and analysts can experiment without the friction of moving data between systems or worrying about inconsistent definitions.",[],{"_key":7783,"_type":99,"children":7784,"markDefs":7789,"style":107},"ba5680faaf2e",[7785],{"_key":7786,"_type":103,"marks":7787,"text":7788},"b461cab41a88",[],"Common early AI wins include improved demand forecasting based on combined internal and external data, churn prediction models that draw on behaviour across multiple channels, or intelligent document processing that turns unstructured content into searchable, analysable data. Because these all live on the same Databricks platform, they benefit from shared governance through Unity Catalog and common engineering standards.",[],{"_key":7791,"_type":99,"children":7792,"markDefs":7797,"style":107},"743ddb2c4d1b",[7793],{"_key":7794,"_type":103,"marks":7795,"text":7796},"37c26a7b374c",[],"To keep that value growing, treat AI as a product, not a collection of one-off experiments. That means clear ownership, monitoring of model performance, processes for retraining and strong guidelines around fairness, transparency and compliance. 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you are a Bulgarian company using Google Meet, you have likely experienced the limitations of default transcription models specifically for Bulgarian speech. We certainly did. At Cosmos Thrace, this pushed us to look for a more robust Bulgarian speech-to-text solution capable of handling noisy, overlapping, real-time audio streams.",[],{"_key":8728,"_type":99,"children":8729,"markDefs":8734,"style":107},"a4c65b487ab0",[8730],{"_key":8731,"_type":103,"marks":8732,"text":8733},"9b4f3a33c8b3",[],"We evaluated multiple transcription models and found that Whisper V3 Turbo offered the best balance between computational cost and transcription accuracy across our benchmarks. Although Whisper was originally released in 2022, it remains highly relevant. Its large-scale weakly supervised training makes it particularly robust to accents, background noise, and varied recording conditions [1]. The active faster-whisper community has further improved performance and usability, making the model fast and practical for production environments.",[],{"_key":8736,"_type":99,"children":8737,"markDefs":8742,"style":107},"9f59fd07db4b",[8738],{"_key":8739,"_type":103,"marks":8740,"text":8741},"8c29db82133c",[],"For our use case, Whisper delivered consistently strong results, however, when reviewing the transcripts more closely, we noticed multiple recurring, easily correctable errors. While minor at first glance, these mistakes became an obstacle during downstream tasks such as named entity recognition and even during simple transcript review. Even the strongest ASR systems tend to produce systematic errors, especially in real-world conversational audio, which we describe in the next section. Recent research shows that large language models can act as effective post-processors for speech transcripts, correcting recognition errors and improving overall readability without modifying the underlying speech model [2,3]. This led us to ask a simple question: could we use a Bulgarian language model to post-process and refine Whisper’s output?",[],{"_key":8744,"_type":99,"children":8745,"markDefs":8758,"style":107},"d946d0795371",[8746,8750,8754],{"_key":8747,"_type":103,"marks":8748,"text":8749},"c0386b57ae5c",[],"To explore this, we experimented with the latest BgGPT model based on Gemma 3, along with 10 other open-weight and closed proprietary models. We evaluated them on both internal datasets and publicly available data that we manually labeled for benchmarking purposes. Our conclusion was clear. The newest iteration of BgGPT is the ",{"_key":8751,"_type":103,"marks":8752,"text":8753},"69947010496f",[3055,4464],"best fit for our production needs",{"_key":8755,"_type":103,"marks":8756,"text":8757},"b0d4ea80f2d8",[]," and likely for many other Bulgarian-language applications as well.",[],{"_createdAt":8760,"_id":8761,"_key":8762,"_ref":8761,"_rev":8763,"_system":8764,"_type":168,"_updatedAt":8767,"afterTextLevel":170,"background":161,"bckg":161,"bigText":8768,"bigTextLevel":171,"button":8769,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":8770,"descriptionLevel":799,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-26T17:12:46Z","9b6e932a-5cac-4afa-92bf-3a9798dfe32d","a5d299b6d8e0","8MCr9b5s1vqlKKaLYtsSY2",{"base":8765},{"id":8761,"rev":8766},"8MCr9b5s1vqlKKaLYtjIvo","2026-02-26T20:44:15Z","Recognizing issues in Bulgarian ASR",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[8771,8779,8787,8795,8811,8819,8831,8839,8847,8855,8863,8871,8883,8891,8899,8907,8919,8927,8939,8963,8971,8979,9011,9023,9031,9043,9051,9059,9067,9084,9092],{"_key":8772,"_type":99,"children":8773,"markDefs":8778,"style":107},"f39fe77cae12",[8774],{"_key":8775,"_type":103,"marks":8776,"text":8777},"7d2a53be5194",[],"Throughout our explorations of Whisper and other SST models, we observed that errors fall into 5 main categories, ranking them from easy to extremely improbable to fix via LLM:",[],{"_key":8780,"_type":99,"children":8781,"markDefs":8786,"style":170},"d34709aa962b",[8782],{"_key":8783,"_type":103,"marks":8784,"text":8785},"e88cf22afb04",[],"Grammatical and Spelling Errors",[],{"_key":8788,"_type":99,"children":8789,"markDefs":8794,"style":107},"e660e54e42f4",[8790],{"_key":8791,"_type":103,"marks":8792,"text":8793},"9347aac0c996",[],"Often, Whisper messes up the grammar or spelling of certain words. The most common mistakes include mixing the subject and non-subject forms of the articles, wrongly substituting often mistaken sounds like “о” vs “у” or “м” vs “н”, and most often names of places, people and institutions. We argue that due to Whisper’s size, the model’s internal reasoning does not go beyond direct transcription and these mistakes are more prominent when the speaker makes phonetic errors, as the model will not correct them by default. Take a look at these examples:",[],{"_key":8796,"_type":8797,"asset":8798},"7bf9c29a32e8","videoFile",{"_createdAt":8799,"_id":8800,"_rev":8801,"_type":8802,"_updatedAt":8799,"assetId":8803,"extension":8804,"mimeType":8805,"originalFilename":8806,"path":8807,"sha1hash":8803,"size":8808,"uploadId":8809,"url":8810},"2026-02-26T20:04:57Z","file-8da69e2a02e05e9e5268d34ce24929e3f7c9499c-mp4","8MCr9b5s1vqlKKaLYtT1Su","sanity.fileAsset","8da69e2a02e05e9e5268d34ce24929e3f7c9499c","mp4","video/mp4","gramatical_zasedanie.mp4","files/wn2c54m4/production/8da69e2a02e05e9e5268d34ce24929e3f7c9499c.mp4",1824163,"omhDJicQYOYvAhWTDOwfCJfjvSF4wmkZ","https://cdn.sanity.io/files/wn2c54m4/production/8da69e2a02e05e9e5268d34ce24929e3f7c9499c.mp4",{"_key":8812,"_type":99,"children":8813,"markDefs":8818,"style":107},"516835a164ee",[8814],{"_key":8815,"_type":103,"marks":8816,"text":8817},"99cc62f9ccce",[],"Instead of “Член 22-ри, алинея 6-та”, it recognizes “член 22 -я, линея 6 то”, which is very close, but incorrect.",[],{"_key":8820,"_type":8797,"asset":8821},"36afd1f3ebe7",{"_createdAt":8822,"_id":8823,"_rev":8824,"_type":8802,"_updatedAt":8822,"assetId":8825,"extension":8804,"mimeType":8805,"originalFilename":8826,"path":8827,"sha1hash":8825,"size":8828,"uploadId":8829,"url":8830},"2026-02-26T20:05:20Z","file-ff683850d315fd56d81cfadc76ed206753489e66-mp4","YijrbTpXUG1P453VSS6bKk","ff683850d315fd56d81cfadc76ed206753489e66","pravopisna_cosmos.mp4","files/wn2c54m4/production/ff683850d315fd56d81cfadc76ed206753489e66.mp4",430604,"koEKvJTaVLvC69to9Re2URHfZa75JW6B","https://cdn.sanity.io/files/wn2c54m4/production/ff683850d315fd56d81cfadc76ed206753489e66.mp4",{"_key":8832,"_type":99,"children":8833,"markDefs":8838,"style":107},"29ad252201db",[8834],{"_key":8835,"_type":103,"marks":8836,"text":8837},"4b612bf1ab53",[],"This is trickier, since “Деплой” is a transliteration of a foreign word. Nevertheless, “деплони” is not an existing word, and should be corrected to “деплойне” or possibly “deploy-не”.",[],{"_key":8840,"_type":99,"children":8841,"markDefs":8846,"style":107},"b8787304e148",[8842],{"_key":8843,"_type":103,"marks":8844,"text":8845},"df7971f6d381",[],"We believe these errors are the easiest to fix without listening to the audio, often also without any context, as the Bulgarian language has rigid rules that are universal. As we already noted, the speakers themselves make a substantial amount of such mistakes, but in our use case, we want to correct these errors as well.",[],{"_key":8848,"_type":99,"children":8849,"markDefs":8854,"style":170},"7a21b88b6017",[8850],{"_key":8851,"_type":103,"marks":8852,"text":8853},"44d08f7636c3",[],"Hallucinated Words",[],{"_key":8856,"_type":99,"children":8857,"markDefs":8862,"style":107},"fc67aa8130b5",[8858],{"_key":8859,"_type":103,"marks":8860,"text":8861},"ea97962be84c",[],"Whisper’s transcription can seldom contain words or whole phrases and sentences that were not actually spoken. This can result in some humorous additions. We are guessing that the training data included subtitles from popular shows, or videos, and perhaps often at the end of such, there are a “Абонирайте се” (Subscribe!) or “Благодаря че изгледахте” (Thank you for watching), “Субтитри от Х” (Subtitles by X).",[],{"_key":8864,"_type":99,"children":8865,"markDefs":8870,"style":107},"c5789190e4d1",[8866],{"_key":8867,"_type":103,"marks":8868,"text":8869},"d154eb0eccff",[],"We caught this behaviour in the following news segment:",[],{"_key":8872,"_type":8797,"asset":8873},"0834b2df1937",{"_createdAt":8874,"_id":8875,"_rev":8876,"_type":8802,"_updatedAt":8874,"assetId":8877,"extension":8804,"mimeType":8805,"originalFilename":8878,"path":8879,"sha1hash":8877,"size":8880,"uploadId":8881,"url":8882},"2026-02-26T20:25:03Z","file-95e16cf4804a8852e7b57c6f0c9c275534c3785d-mp4","8MCr9b5s1vqlKKaLYtjHPw","95e16cf4804a8852e7b57c6f0c9c275534c3785d","hallucinated_news.mp4","files/wn2c54m4/production/95e16cf4804a8852e7b57c6f0c9c275534c3785d.mp4",14845560,"VyHP0yr742XChluMXeQQeEzTdXByf1u3","https://cdn.sanity.io/files/wn2c54m4/production/95e16cf4804a8852e7b57c6f0c9c275534c3785d.mp4",{"_key":8884,"_type":99,"children":8885,"markDefs":8890,"style":107},"d94824e10ba8",[8886],{"_key":8887,"_type":103,"marks":8888,"text":8889},"96b60d786b5b",[],"This is generally easy to fix, as hallucinated segments are trivially identifiable as they appear out of context or as incoherent speech.",[],{"_key":8892,"_type":99,"children":8893,"markDefs":8898,"style":170},"e04f30cca3c7",[8894],{"_key":8895,"_type":103,"marks":8896,"text":8897},"5876327e65d6",[],"Major Phonetic Errors",[],{"_key":8900,"_type":99,"children":8901,"markDefs":8906,"style":107},"0a755c327258",[8902],{"_key":8903,"_type":103,"marks":8904,"text":8905},"019ec8e73ea1",[],"More exaggerated transcription mistakes can occur when there are multiple speakers, the speaker talks quickly, with few pauses or even slurs their words.",[],{"_key":8908,"_type":8797,"asset":8909},"dbe28eb57b2c",{"_createdAt":8910,"_id":8911,"_rev":8912,"_type":8802,"_updatedAt":8910,"assetId":8913,"extension":8804,"mimeType":8805,"originalFilename":8914,"path":8915,"sha1hash":8913,"size":8916,"uploadId":8917,"url":8918},"2026-02-26T20:06:35Z","file-3e706576b21994418529d6d7d991ddb625dbf542-mp4","3rPJjKxLmE5pnUqM0N0Oal","3e706576b21994418529d6d7d991ddb625dbf542","phonetic_zasedanie.mp4","files/wn2c54m4/production/3e706576b21994418529d6d7d991ddb625dbf542.mp4",1681714,"94ZDPfeTbML94XIMJ211LxRensIhTNVC","https://cdn.sanity.io/files/wn2c54m4/production/3e706576b21994418529d6d7d991ddb625dbf542.mp4",{"_key":8920,"_type":99,"children":8921,"markDefs":8926,"style":107},"4d8bd6374931",[8922],{"_key":8923,"_type":103,"marks":8924,"text":8925},"fd5eeb438fda",[],"In this example, the model confused “Стабилно Народно Събрание” with “стабилна народността брания”, which does sound relatively close. Through a bit of contextual reasoning, this error is fixable by a human and LLM alike. However, there are some cases where a significant amount of context is lost and we deem the mistake irrecoverable.",[],{"_key":8928,"_type":8797,"asset":8929},"a17341b16b7d",{"_createdAt":8930,"_id":8931,"_rev":8932,"_type":8802,"_updatedAt":8930,"assetId":8933,"extension":8804,"mimeType":8805,"originalFilename":8934,"path":8935,"sha1hash":8933,"size":8936,"uploadId":8937,"url":8938},"2026-02-26T20:06:59Z","file-0adef47e39d7bb59f150e19a9ef1abde73460bfc-mp4","3rPJjKxLmE5pnUqM0N0uRP","0adef47e39d7bb59f150e19a9ef1abde73460bfc","phonetic_podcast.mp4","files/wn2c54m4/production/0adef47e39d7bb59f150e19a9ef1abde73460bfc.mp4",1399043,"txpKOer4cJUDhgHeAmt4k33iPm0rFyTY","https://cdn.sanity.io/files/wn2c54m4/production/0adef47e39d7bb59f150e19a9ef1abde73460bfc.mp4",{"_key":8940,"_type":99,"children":8941,"markDefs":8962,"style":107},"1b5a48d6c6cc",[8942,8946,8950,8954,8958],{"_key":8943,"_type":103,"marks":8944,"text":8945},"db2970da6cc3",[],"Here, ",{"_key":8947,"_type":103,"marks":8948,"text":8949},"41e924b602ab",[4464],"“40-50km”",{"_key":8951,"_type":103,"marks":8952,"text":8953},"068ee3593915",[]," is merged as ",{"_key":8955,"_type":103,"marks":8956,"text":8957},"dfdd8cd9ec45",[4464],"“450km”",{"_key":8959,"_type":103,"marks":8960,"text":8961},"2a8ab987bacb",[],". Even such a simple omission is usually catastrophic, since the LLM or even a human reading the transcript cannot reliably know there is a mistake, not to mention guessing the correct interpretation, without audio. Rarely, there are cases where stronger reasoning may conclude that, in this example, 450 may be too much for the context (e.g., walking distance) and argue that the speaker meant 40-50, but it is not robust.",[],{"_key":8964,"_type":99,"children":8965,"markDefs":8970,"style":170},"6a78052b80f9",[8966],{"_key":8967,"_type":103,"marks":8968,"text":8969},"5e62c7b85a2f",[],"Foreign Тerm Мisrecognition",[],{"_key":8972,"_type":99,"children":8973,"markDefs":8978,"style":107},"a9f405efbbab",[8974],{"_key":8975,"_type":103,"marks":8976,"text":8977},"fe15ab2b3084",[],"While delving into the nuances of robust ASR, we wondered about the rules of intermixing foreign words without translation, as it does not even qualify as standard Bulgarian formally. In technologically-related conversations, we often use English terms, which do not have convenient translations. Moreover, mixing in English words has become increasingly common in modern Bulgarian speech. It is difficult for models to recognize this code-switching phenomenon and it presents one of the greatest challenges for this task.",[],{"_key":8980,"_type":99,"children":8981,"markDefs":9010,"style":107},"cb80e397705b",[8982,8986,8990,8994,8998,9002,9006],{"_key":8983,"_type":103,"marks":8984,"text":8985},"61e816d754a0",[],"As far as orthography goes, the most accepted method for the incorporation of such words and phrases is to phonologically map them and apply the grammatically appropriate suffixes. For example, ",{"_key":8987,"_type":103,"marks":8988,"text":8989},"1054dc5176f6",[4464],"“to dockerize”",{"_key":8991,"_type":103,"marks":8992,"text":8993},"a41352a7e22c",[]," would be transformed into ",{"_key":8995,"_type":103,"marks":8996,"text":8997},"fe2a1a48df8e",[4464],"“да докърайзне”",{"_key":8999,"_type":103,"marks":9000,"text":9001},"fc76b8a6b640",[],". The option ",{"_key":9003,"_type":103,"marks":9004,"text":9005},"f7ef5c934ac2",[4464],"“да dockerize-не”",{"_key":9007,"_type":103,"marks":9008,"text":9009},"e48eb29ef2f8",[]," is also accepted.",[],{"_key":9012,"_type":8797,"asset":9013},"33848014753c",{"_createdAt":9014,"_id":9015,"_rev":9016,"_type":8802,"_updatedAt":9014,"assetId":9017,"extension":8804,"mimeType":8805,"originalFilename":9018,"path":9019,"sha1hash":9017,"size":9020,"uploadId":9021,"url":9022},"2026-02-26T20:07:28Z","file-73c6840934c361c0dc45992d2c7b98f94c0474d6-mp4","8MCr9b5s1vqlKKaLYtVcSW","73c6840934c361c0dc45992d2c7b98f94c0474d6","ang_termin_cosmos.mp4","files/wn2c54m4/production/73c6840934c361c0dc45992d2c7b98f94c0474d6.mp4",580332,"aJbJV37b4SUoJ7LmQNMEcXEM3b2VslFo","https://cdn.sanity.io/files/wn2c54m4/production/73c6840934c361c0dc45992d2c7b98f94c0474d6.mp4",{"_key":9024,"_type":99,"children":9025,"markDefs":9030,"style":107},"9a5c83ea967a",[9026],{"_key":9027,"_type":103,"marks":9028,"text":9029},"4c3567c1e14b",[],"Here, the developer obviously meant “dev” as the branch name, but Whisper transcribed it as “ДЕФ”.",[],{"_key":9032,"_type":8797,"asset":9033},"1ad1fb103dcd",{"_createdAt":9034,"_id":9035,"_rev":9036,"_type":8802,"_updatedAt":9034,"assetId":9037,"extension":8804,"mimeType":8805,"originalFilename":9038,"path":9039,"sha1hash":9037,"size":9040,"uploadId":9041,"url":9042},"2026-02-26T20:07:49Z","file-ad87f36e2e4f3142e953750983829d4df84bb7e2-mp4","YijrbTpXUG1P453VSS9cHC","ad87f36e2e4f3142e953750983829d4df84bb7e2","ang_termin_zasedanie.mp4","files/wn2c54m4/production/ad87f36e2e4f3142e953750983829d4df84bb7e2.mp4",950148,"Ormg4K49ij4b3DBXldHE4c5v70c46FkB","https://cdn.sanity.io/files/wn2c54m4/production/ad87f36e2e4f3142e953750983829d4df84bb7e2.mp4",{"_key":9044,"_type":99,"children":9045,"markDefs":9050,"style":107},"3cd76e8415a4",[9046],{"_key":9047,"_type":103,"marks":9048,"text":9049},"0c6cab58c0b5",[],"For this example, we have to admit, we were unsure what the person meant, but a strong reasoning model such as Anthropic’s Opus figured it out - it was the website strategy.bg, which it determined only based on the context!",[],{"_key":9052,"_type":99,"children":9053,"markDefs":9058,"style":170},"9293c19ae7ec",[9054],{"_key":9055,"_type":103,"marks":9056,"text":9057},"cfd5375a1281",[],"Missed Words",[],{"_key":9060,"_type":99,"children":9061,"markDefs":9066,"style":107},"ac8f4091519c",[9062],{"_key":9063,"_type":103,"marks":9064,"text":9065},"9fbad881f4ab",[],"A case that can become impossible to fix is when Whisper simply omits words without a clear pattern. Most often, these are connecting words that carry little context, which is not an issue. Still, to be true to the audio, we are expected to add them. But it is not trivial for the LLM to spawn them.",[],{"_key":9068,"_type":8797,"asset":9069,"file":9081},"f0dc90ae64b2",{"_createdAt":9070,"_id":9071,"_rev":9072,"_type":8802,"_updatedAt":9070,"assetId":9073,"extension":9074,"mimeType":9075,"originalFilename":9076,"path":9077,"sha1hash":9073,"size":9078,"uploadId":9079,"url":9080},"2026-02-26T15:28:46Z","file-9abd4b6702f0d303737b27635e7d15ab64826434-mkv","3rPJjKxLmE5pnUqM0In32b","9abd4b6702f0d303737b27635e7d15ab64826434","mkv","video/matroska","izpusnati_dumi_podcast.mkv","files/wn2c54m4/production/9abd4b6702f0d303737b27635e7d15ab64826434.mkv",8873266,"nuGPp5bm7xSRMJ4ndrQoXSySQ6AWoF4M","https://cdn.sanity.io/files/wn2c54m4/production/9abd4b6702f0d303737b27635e7d15ab64826434.mkv",{"_type":9082,"asset":9083},"file",{"_ref":9071,"_type":84},{"_key":9085,"_type":99,"children":9086,"markDefs":9091,"style":107},"965ca4613405",[9087],{"_key":9088,"_type":103,"marks":9089,"text":9090},"fc0cf7a548d8",[],"In this example, a lot of connecting words are lost, but generally, they do not carry major context. Rarely does it happen that crucial words to the meaning are omitted, which renders the correct transcript irrecoverable.",[],{"_key":9093,"_type":99,"children":9094,"markDefs":9099,"style":107},"6d3127b08bab",[9095],{"_key":9096,"_type":103,"marks":9097,"text":9098},"119b8b647caa",[],"Practical Note: If you notice a lot of missed words, this is most probably a VAD filter setting, not a model problem. One has to create a balance between hallucinated words in sections without speech (no VAD filter) and missed words (strict VAD filter). This should be fine-tuned based on the use-case.",[],{"_createdAt":9101,"_id":9102,"_key":9103,"_ref":9102,"_rev":9104,"_system":9105,"_type":168,"_updatedAt":9108,"afterTextLevel":170,"background":161,"bckg":161,"bigText":9109,"bigTextLevel":171,"button":9110,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":9111,"descriptionLevel":799,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-26T18:12:07Z","48cd0152-8756-4a30-ab97-d8b943772fbf","797637ad5f90","YijrbTpXUG1P453VSSfkqQ",{"base":9106},{"id":9102,"rev":9107},"8MCr9b5s1vqlKKaLYtinBe","2026-02-26T20:45:03Z","Experiments",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[9112,9120,9128,9136,9144,9152,9171,9179,9187,9195,9203,9211,9219,9227,9235,9243,9251,9259,9267,9275,9311,9319,9356,9364,9372,9409],{"_key":9113,"_type":99,"children":9114,"markDefs":9119,"style":170},"b113fce93485",[9115],{"_key":9116,"_type":103,"marks":9117,"text":9118},"cb31890a24da",[],"ASR fixing instructions",[],{"_key":9121,"_type":99,"children":9122,"markDefs":9127,"style":107},"1710adc51aa9",[9123],{"_key":9124,"_type":103,"marks":9125,"text":9126},"862b9794cd7f",[],"Our LLM prompt is composed of general rules, anecdotal examples to elicit few-shot learning, the transcript lines (3-5) to be fixed as well as some of the context around it.",[],{"_key":9129,"_type":99,"children":9130,"markDefs":9135,"style":170},"91fe8cb32230",[9131],{"_key":9132,"_type":103,"marks":9133,"text":9134},"94ba62a7e2c8",[],"Test data sources",[],{"_key":9137,"_type":99,"children":9138,"markDefs":9143,"style":107},"a9b6478fd4a1",[9139],{"_key":9140,"_type":103,"marks":9141,"text":9142},"936524feedf7",[],"In our test dataset, we included a parliamentary recording, a podcast, news recordings, and internal meetings. We have publicly shared the datasets with a permissible license.",[],{"_key":9145,"_type":99,"children":9146,"markDefs":9151,"style":170},"5b6ddfab14a3",[9147],{"_key":9148,"_type":103,"marks":9149,"text":9150},"e5906a58469f",[],"STT model",[],{"_key":9153,"_type":99,"children":9154,"markDefs":9168,"style":107},"669b10914960",[9155,9159,9164],{"_key":9156,"_type":103,"marks":9157,"text":9158},"20fcc299c323",[],"We use ",{"_key":9160,"_type":103,"marks":9161,"text":9163},"6610d3fc9630",[9162],"c1c94d32e9ad","faster-whisper’s Turbo variant",{"_key":9165,"_type":103,"marks":9166,"text":9167},"bbfa0badd99e",[],", running at FP16 precision, to transcribe the audio files.",[9169],{"_key":9162,"_type":173,"href":9170},"https://huggingface.co/Systran/faster-distil-whisper-large-v3",{"_key":9172,"_type":99,"children":9173,"markDefs":9178,"style":170},"ebf59deb580e",[9174],{"_key":9175,"_type":103,"marks":9176,"text":9177},"f731f7893c61",[],"Test data validation",[],{"_key":9180,"_type":99,"children":9181,"markDefs":9186,"style":107},"5cb0774d427a",[9182],{"_key":9183,"_type":103,"marks":9184,"text":9185},"271d442bf47f",[],"We manually go through the raw Whisper transcripts in parallel with the audio and correct errors, abiding by the established rules.",[],{"_key":9188,"_type":99,"children":9189,"markDefs":9194,"style":107},"de09da328f09",[9190],{"_key":9191,"_type":103,"marks":9192,"text":9193},"64e6242bbdff",[],"In our initial attempt, we noticed that letting an LLM model go through the transcript first introduces a lot of biases, and the final results may be skewed towards certain models that match its writing style.",[],{"_key":9196,"_type":99,"children":9197,"markDefs":9202,"style":107},"13343ecd5f86",[9198],{"_key":9199,"_type":103,"marks":9200,"text":9201},"bb647f13ea2c",[],"We then compare the human-redacted text with the LLM redacted text and remove any remaining mistakes we saw. We settle on a few rules for edge cases (also included in the model instructions):",[],{"_key":9204,"_type":99,"children":9205,"level":230,"listItem":4889,"markDefs":9210,"style":107},"94d4ff20c216",[9206],{"_key":9207,"_type":103,"marks":9208,"text":9209},"bb367463e8db",[],"Website names should be written in Latin.",[],{"_key":9212,"_type":99,"children":9213,"level":230,"listItem":4889,"markDefs":9218,"style":107},"ed15b19da58d",[9214],{"_key":9215,"_type":103,"marks":9216,"text":9217},"160b0875cf42",[],"Product names should be written in Latin (e.g., “Docker”, “Python”, “.NET”).",[],{"_key":9220,"_type":99,"children":9221,"level":230,"listItem":4889,"markDefs":9226,"style":107},"3b96a8ae8352",[9222],{"_key":9223,"_type":103,"marks":9224,"text":9225},"d59f7b4ffaff",[],"Always use the correct article (subject vs non-subject), even if the speaker pronounced it otherwise.",[],{"_key":9228,"_type":99,"children":9229,"level":230,"listItem":4889,"markDefs":9234,"style":107},"36ac40acb3be",[9230],{"_key":9231,"_type":103,"marks":9232,"text":9233},"0525d3b6e941",[],"Verbalization of foreign terms should stay in Cyrillic (e.g., “докеризация”, “пулване”, “пушване”)",[],{"_key":9236,"_type":99,"children":9237,"level":230,"listItem":4889,"markDefs":9242,"style":107},"aaaa1ffe461d",[9238],{"_key":9239,"_type":103,"marks":9240,"text":9241},"0a78ef2efb62",[],"No adding or removing filler words, unless they are crucial for the understanding or correcting significantly malformed sentences.",[],{"_key":9244,"_type":99,"children":9245,"markDefs":9250,"style":107},"34d52b6644b1",[9246],{"_key":9247,"_type":103,"marks":9248,"text":9249},"1aa62078da72",[],"Potentially, some errors remain, or cases where it is too ambiguous to decide on the correct form and annotator bias was introduced, but we believe that the signal is good enough for us to make a reasonable correlation. We provide the transcribed and redacted data below.",[],{"_key":9252,"_type":99,"children":9253,"markDefs":9258,"style":170},"1de8af67f388",[9254],{"_key":9255,"_type":103,"marks":9256,"text":9257},"5e0181c2aaa0",[],"Metrics",[],{"_key":9260,"_type":99,"children":9261,"markDefs":9266,"style":107},"1ca878b192a1",[9262],{"_key":9263,"_type":103,"marks":9264,"text":9265},"9f8e4bf0dcb3",[],"One of the more commonly used metrics for judging the quality of ASR is WER (Word Error Rate), or the percentage of words that were not correctly written, based on edit distance, compared to the ground truth.",[],{"_key":9268,"_type":99,"children":9269,"markDefs":9274,"style":107},"d6fb156531fc",[9270],{"_key":9271,"_type":103,"marks":9272,"text":9273},"1e64d3ae8b21",[],"In the example below, we can see that BgGPT omits a “си”, erroneously replaces the word “мисля” with “смятам” (which is not perfect but at least grammatically correct) and makes an arguable mistake of the word “перформънс” (performance). So in this case, the edit distance in terms of words is equal to 3. Given that the total number of words in this cue is 14, WER = 3/14 = 0.214. While the mistakes for Gemini are different, it also receives the same WER.",[],{"_key":9276,"_type":81,"alt":9277,"asset":9278},"049dcd1a020e","WER Example",{"_createdAt":9279,"_id":9280,"_rev":9281,"_type":114,"_updatedAt":9279,"assetId":9282,"extension":116,"metadata":9283,"mimeType":153,"originalFilename":9306,"path":9307,"sha1hash":9282,"size":9308,"uploadId":9309,"url":9310},"2026-02-26T20:22:51Z","image-8392ad3d0d16226f60f29fd02f35cab4cda21f85-1192x91-png","8MCr9b5s1vqlKKaLYtiie2","8392ad3d0d16226f60f29fd02f35cab4cda21f85",{"_type":118,"blurHash":9284,"dimensions":9285,"hasAlpha":126,"isOpaque":126,"lqip":9289,"palette":9290,"thumbHash":9305},"404nxx1vv2L1#m",{"_type":121,"aspectRatio":9286,"height":9287,"width":9288},13.098901098901099,91,1192,"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAACCAYAAABYBvyLAAAACXBIWXMAABYlAAAWJQFJUiTwAAAAeUlEQVR4nB3IMRLCIBBA0dQJRUhkIctCEIxjpeP9D/ed8ZVvEhG897hlwTlHCIGcM2ZGO5RHjFylcI1B753WGmet3EvhZcbHjK8qbxH6ujKllIgi7PvO5jfCLSBB/qciWAhUVUotZDOyKnocaEqcqoysPKMwvEfmmR8rMzPBWgGnJQAAAABJRU5ErkJggg==",{"_type":129,"darkMuted":9291,"darkVibrant":9294,"dominant":9296,"lightMuted":9297,"lightVibrant":9299,"muted":9301,"vibrant":9303},{"_type":131,"background":9292,"foreground":133,"population":9293,"title":133},"#693439",2.64,{"_type":131,"background":9295,"foreground":133,"population":144,"title":133},"#612229",{"_type":131,"background":9292,"foreground":133,"population":9293,"title":133},{"_type":131,"background":9298,"foreground":133,"population":134,"title":133},"#692f36",{"_type":131,"background":9300,"foreground":140,"population":134,"title":133},"#d5a3a9",{"_type":131,"background":9302,"foreground":133,"population":6131,"title":133},"#885155",{"_type":131,"background":9304,"foreground":133,"population":147,"title":133},"#843c44","BwgGAYJViXpmdwh3sGoFq1Y=","wer_example.PNG","images/wn2c54m4/production/8392ad3d0d16226f60f29fd02f35cab4cda21f85-1192x91.png",18892,"Bn6KwAAlgK3H7tRNH3bNjtYkzcBtmn9z","https://cdn.sanity.io/images/wn2c54m4/production/8392ad3d0d16226f60f29fd02f35cab4cda21f85-1192x91.png",{"_key":9312,"_type":99,"children":9313,"markDefs":9318,"style":107},"37238904b9ed",[9314],{"_key":9315,"_type":103,"marks":9316,"text":9317},"cbf06bf6dd8c",[],"We showcase WER and subsequently, WER Reduction % (or what percent of the errors did we manage to remove). Normalized WER refers to the normalization of the words before the calculation - lower case, removed punctuation, etc.",[],{"_key":9320,"_type":81,"alt":9321,"asset":9322,"caption":9321},"2baf73174acb","Overal Raw WER vs Overal Normalized WER",{"_createdAt":9323,"_id":9324,"_rev":9325,"_type":114,"_updatedAt":9323,"assetId":9326,"extension":116,"metadata":9327,"mimeType":153,"originalFilename":9351,"path":9352,"sha1hash":9326,"size":9353,"uploadId":9354,"url":9355},"2026-02-26T20:11:07Z","image-78db4a3e0be69f529916a53ca4922d504d00afd4-15831x7316-png","uS4QuMfQxT2EdbLDoXtAFl","78db4a3e0be69f529916a53ca4922d504d00afd4",{"_type":118,"blurHash":9328,"dimensions":9329,"hasAlpha":126,"isOpaque":126,"lqip":9333,"palette":9334,"thumbHash":9350},"MuOW:BxZa$${xtxuofj[oyWW~oWYj?NfRl",{"_type":121,"aspectRatio":9330,"height":9331,"width":9332},2.163887370147622,7316,15831,"data:image/png;base64,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",{"_type":129,"darkMuted":9335,"darkVibrant":9337,"dominant":9339,"lightMuted":9342,"lightVibrant":9345,"muted":9347,"vibrant":9349},{"_type":131,"background":9336,"foreground":133,"population":134,"title":133},"#2c443c",{"_type":131,"background":9338,"foreground":133,"population":134,"title":133},"#133f71",{"_type":131,"background":9340,"foreground":133,"population":9341,"title":133},"#488fe0",6.75,{"_type":131,"background":9343,"foreground":140,"population":9344,"title":133},"#b7ccdc",2.8,{"_type":131,"background":9346,"foreground":140,"population":5555,"title":133},"#5cbcfc",{"_type":131,"background":9348,"foreground":133,"population":5555,"title":133},"#5986a1",{"_type":131,"background":9340,"foreground":133,"population":9341,"title":133},"c+cNG4KImXeIiPeHa4jPd/g=","wer_raw_vs_norm.png","images/wn2c54m4/production/78db4a3e0be69f529916a53ca4922d504d00afd4-15831x7316.png",2257486,"KAUxiA2eIdkotqxay7BAvV7JPem8AFfX","https://cdn.sanity.io/images/wn2c54m4/production/78db4a3e0be69f529916a53ca4922d504d00afd4-15831x7316.png",{"_key":9357,"_type":99,"children":9358,"markDefs":9363,"style":107},"4dce9c2c18fb",[9359],{"_key":9360,"_type":103,"marks":9361,"text":9362},"ea881884ea93",[],"As we can see, BgGPT consistently outperformed all open-weight models, even significantly larger and reasoning-capable ones like DeepSeek v3.2. While the SOTA closed models that perform reasoning may be competitive or slightly better, the gap is relatively small and with adjustments to the prompt techniques and domain-relevant lexicons, we believe it can be closed even further. Nevertheless, on observation of the corrections, Gemini is very robust to different prompts and, due to its strong reasoning capabilities, is able to detect some subtle errors, as mentioned above, that BgGPT 27B may struggle with. Meanwhile, BgGPT can catch some grammatical and spelling errors that the other models don’t, simply because it is better adapted to the Bulgarian language. The greatest example of this is words like “оттук”, “навреме”, etc., which both Whisper and the other models leave incorrectly separated.",[],{"_key":9365,"_type":99,"children":9366,"markDefs":9371,"style":107},"c53409156446",[9367],{"_key":9368,"_type":103,"marks":9369,"text":9370},"80faa9cf27fe",[],"NOTE: The BgGPT model used in the experiments is the quantized FP8 version, which is not worse than its original BF16 version but is significantly faster and cheaper.",[],{"_key":9373,"_type":81,"alt":9374,"asset":9375,"caption":9374},"dc3292202525","WER Improvement over Whisper Raw 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Processing",{"_createdAt":9431,"_id":9432,"_rev":9433,"_type":114,"_updatedAt":9431,"assetId":9434,"extension":116,"metadata":9435,"mimeType":153,"originalFilename":9458,"path":9459,"sha1hash":9434,"size":9460,"uploadId":9461,"url":9462},"2026-02-26T20:14:36Z","image-1aaae6ba88b6079667e820f85eb4751859a9fbc2-11904x6064-png","YijrbTpXUG1P453VSSIh62","1aaae6ba88b6079667e820f85eb4751859a9fbc2",{"_type":118,"blurHash":9436,"dimensions":9437,"hasAlpha":126,"isOpaque":126,"lqip":9441,"palette":9442,"thumbHash":9457},"MRRC_GIV?a-o%M~qs:IUNGRjMx%LxvNGRj",{"_type":121,"aspectRatio":9438,"height":9439,"width":9440},1.963060686015831,6064,11904,"data:image/png;base64,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",{"_type":129,"darkMuted":9443,"darkVibrant":9445,"dominant":9447,"lightMuted":9450,"lightVibrant":9452,"muted":9454,"vibrant":9456},{"_type":131,"background":9444,"foreground":133,"population":134,"title":133},"#44443c",{"_type":131,"background":9446,"foreground":133,"population":134,"title":133},"#123d71",{"_type":131,"background":9448,"foreground":133,"population":9449,"title":133},"#4b8ee1",2.93,{"_type":131,"background":9451,"foreground":140,"population":2995,"title":133},"#c5c5b9",{"_type":131,"background":9453,"foreground":140,"population":147,"title":133},"#6caffa",{"_type":131,"background":9455,"foreground":133,"population":134,"title":133},"#546ca4",{"_type":131,"background":9448,"foreground":133,"population":9449,"title":133},"+fcFBIDVuoqPZHalamTQnQ7u+g==","cost_per_hour.png","images/wn2c54m4/production/1aaae6ba88b6079667e820f85eb4751859a9fbc2-11904x6064.png",961868,"qV3XRQ9ArCAZ8yFGKksQLfe2tNl8XPkW","https://cdn.sanity.io/images/wn2c54m4/production/1aaae6ba88b6079667e820f85eb4751859a9fbc2-11904x6064.png",{"_key":9464,"_type":99,"children":9465,"markDefs":9470,"style":107},"541faa17afb1",[9466],{"_key":9467,"_type":103,"marks":9468,"text":9469},"e67a7e914b38",[],"Processing one hour of transcripts with BgGPT costs roughly $0.03, similarly to Gemma-3. The same hour costs $0.33 with Gemini 3 Flash, $1.36 with GPT-5.2, and $1.79 with Claude Sonnet 4.5. When you're running these AI flows at scale, that difference adds up fast. For example, if we choose Gemini 3 Flash as our model of choice, we can expect an API bill of 330$ for 1000h of transcripts, compared to 33$ for BgGPT.",[],{"_key":9472,"_type":99,"children":9473,"markDefs":9477,"style":107},"e4ced8b45b2a",[9474],{"_key":9467,"_type":103,"marks":9475,"text":9476},[],"\nThis is why when we consider price/performance, BgGPT is the clear winner.",[],{"_key":9479,"_type":81,"alt":9480,"asset":9481,"caption":9480},"b24cf372710a","Price per 10% WER Reduction in 1h of Video",{"_createdAt":9482,"_id":9483,"_rev":9484,"_type":114,"_updatedAt":9482,"assetId":9485,"extension":116,"metadata":9486,"mimeType":153,"originalFilename":9506,"path":9507,"sha1hash":9485,"size":9508,"uploadId":9509,"url":9510},"2026-02-26T20:15:54Z","image-d31eeb71d14a9e5f083ccaed5bce9d1c0a1a9a19-11904x6064-png","YijrbTpXUG1P453VSSKU54","d31eeb71d14a9e5f083ccaed5bce9d1c0a1a9a19",{"_type":118,"blurHash":9487,"dimensions":9488,"hasAlpha":126,"isOpaque":126,"lqip":9489,"palette":9490,"thumbHash":9505},"MLRpB^IU-;?H?a~qxaM{IUIUIA%L%MRjRk",{"_type":121,"aspectRatio":9438,"height":9439,"width":9440},"data:image/png;base64,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",{"_type":129,"darkMuted":9491,"darkVibrant":9493,"dominant":9495,"lightMuted":9498,"lightVibrant":9500,"muted":9502,"vibrant":9504},{"_type":131,"background":9492,"foreground":133,"population":147,"title":133},"#504d32",{"_type":131,"background":9494,"foreground":133,"population":134,"title":133},"#163e6d",{"_type":131,"background":9496,"foreground":133,"population":9497,"title":133},"#4c8dda",1.19,{"_type":131,"background":9499,"foreground":140,"population":7526,"title":140},"#dec8c8",{"_type":131,"background":9501,"foreground":140,"population":2312,"title":133},"#5ca4ec",{"_type":131,"background":9503,"foreground":133,"population":147,"title":133},"#68809d",{"_type":131,"background":9496,"foreground":133,"population":9497,"title":133},"+vcFBIC024mfVYWje2VwiR+X+Q==","price_per_10pct_wer.png","images/wn2c54m4/production/d31eeb71d14a9e5f083ccaed5bce9d1c0a1a9a19-11904x6064.png",956063,"ZTM1qWVkhraJe3DDw1iKnki1rk8UcYa2","https://cdn.sanity.io/images/wn2c54m4/production/d31eeb71d14a9e5f083ccaed5bce9d1c0a1a9a19-11904x6064.png",{"_key":9512,"_type":99,"children":9513,"markDefs":9518,"style":107},"4a68668ba106",[9514],{"_key":9515,"_type":103,"marks":9516,"text":9517},"f84c5f3866e4",[],"The qualitative impact was just as important. Before LLM refinement, our transcripts were \"mostly right, but annoying to read.\" Afterwards, they were reliable enough to use directly, without cross-referencing with the audio track. This might sound like a small thing, but it's the difference between transcripts being a byproduct and transcripts being a product.",[],{"_key":9520,"_type":81,"alt":9521,"asset":9522,"caption":9521},"6935c507ae42","WER Improvement over Whisper Raw",{"_createdAt":9523,"_id":9524,"_rev":9525,"_type":114,"_updatedAt":9523,"assetId":9526,"extension":116,"metadata":9527,"mimeType":153,"originalFilename":9553,"path":9554,"sha1hash":9526,"size":9555,"uploadId":9556,"url":9557},"2026-02-26T20:22:15Z","image-915bc88621c1b454cf2254bcb570209915b868b6-5900x4448-png","YijrbTpXUG1P453VSSRP7C","915bc88621c1b454cf2254bcb570209915b868b6",{"_type":118,"blurHash":9528,"dimensions":9529,"hasAlpha":126,"isOpaque":126,"lqip":9533,"palette":9534,"thumbHash":9552},"VaRy52*xxZGb*I.7OGWr$yMyTwl9t7n4m-IWxXt6Irxt",{"_type":121,"aspectRatio":9530,"height":9531,"width":9532},1.3264388489208634,4448,5900,"data:image/png;base64,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",{"_type":129,"darkMuted":9535,"darkVibrant":9538,"dominant":9540,"lightMuted":9543,"lightVibrant":9546,"muted":9549,"vibrant":9551},{"_type":131,"background":9536,"foreground":133,"population":9537,"title":133},"#5a5a5a",0.49,{"_type":131,"background":9539,"foreground":133,"population":134,"title":133},"#810903",{"_type":131,"background":9541,"foreground":133,"population":9542,"title":133},"#fb6058",5.42,{"_type":131,"background":9544,"foreground":140,"population":9545,"title":133},"#ccafaf",0.44,{"_type":131,"background":9547,"foreground":140,"population":9548,"title":133},"#fc7374",2.44,{"_type":131,"background":9550,"foreground":133,"population":8684,"title":133},"#5e86b5",{"_type":131,"background":9541,"foreground":133,"population":9542,"title":133},"NygKJYqU+XmMh3WqaEaIep9J9XhF","bggpt_vs_gemma_comparison.png","images/wn2c54m4/production/915bc88621c1b454cf2254bcb570209915b868b6-5900x4448.png",403512,"h1fW3I6fvqtIfm6gG4IP2kBoxaEW9qCY","https://cdn.sanity.io/images/wn2c54m4/production/915bc88621c1b454cf2254bcb570209915b868b6-5900x4448.png",{"_key":9559,"_type":99,"children":9560,"markDefs":9565,"style":107},"9fe8c40f68fe",[9561],{"_key":9562,"_type":103,"marks":9563,"text":9564},"ae8cdb41a1a4",[],"BgGPT's Bulgarian fine-tuning more than doubled the WER improvement compared to base Gemma 3 27B - 36.4% vs 17.0% — at essentially the same (or even lower in the case of FP8) inference cost. All of this combined made BgGPT the sensible model of choice for our use case.",[],{"_key":9567,"_type":99,"children":9568,"markDefs":9572,"style":107},"4f2806b6fa97",[9569],{"_key":9570,"_type":103,"marks":9571,"text":4420},"3668c5921492",[],[],{"_createdAt":9574,"_id":9575,"_key":9576,"_ref":9575,"_rev":9577,"_system":9578,"_type":168,"_updatedAt":9581,"afterTextLevel":170,"background":161,"bckg":161,"bigText":9582,"bigTextLevel":171,"button":9583,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":9584,"descriptionLevel":799,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-26T18:19:29Z","75c0d286-f733-4ec1-a38f-3a322f003f5b","fb27ad705bd6","3rPJjKxLmE5pnUqM0MpIVs",{"base":9579},{"id":9575,"rev":9580},"8MCr9b5s1vqlKKaLYs6VOc","2026-02-26T19:58:22Z","References",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[9585],{"_key":9586,"_type":99,"children":9587,"markDefs":9628,"style":107},"70f1f531a679",[9588,9592,9597,9601,9606,9610,9615,9619,9624],{"_key":9589,"_type":103,"marks":9590,"text":9591},"93507ddcc8fe",[],"[1] Radford et al., Robust Speech Recognition via Large-Scale Weak Supervision, 2022.\n[2] Yang et al., Generative Speech Recognition Error Correction with Large Language Models, 2023.\n[3] ASR Error Correction using Large Language Models, 2024.\n[4] Courtland et al., Punctuation Restoration using Transformer Models, 2020.\n[5] Burgas TV, \"България избира своите кметове и гласува на референдум,\" YouTube, Oct. 25, 2015. [Online]. Available: ",{"_key":9593,"_type":103,"marks":9594,"text":9596},"1bb98b9cc51f",[9595],"b2c8e5386ab7","https://www.youtube.com/watch?v=MwL_M3oua4k",{"_key":9598,"_type":103,"marks":9599,"text":9600},"8495db4c2118",[],"\n[6] Подкаст Срещи, \"еп. 4 Краси Панчев: Мисиите, които те променят,\" YouTube, Nov. 12, 2025. [Online]. Available: ",{"_key":9602,"_type":103,"marks":9603,"text":9605},"fe19a3790e32",[9604],"34958fd3f5be","https://www.youtube.com/watch?v=f-pS0C3AYa0",{"_key":9607,"_type":103,"marks":9608,"text":9609},"d335b2bb0262",[],"\n[7] Народно събрание на Република България, \"Пленарно заседание на 51-о Народно събрание,\" parliament.bg, Jan. 22, 2026. [Online]. Available: ",{"_key":9611,"_type":103,"marks":9612,"text":9614},"ba06759bfb37",[9613],"8ee868142a78","https://parliament.bg/bg/video/ID/1946",{"_key":9616,"_type":103,"marks":9617,"text":9618},"efb4fe261654",[],"\n[8] Народно събрание на Република България, \"Комисия за прякото участие на гражданите, жалбите и взаимодействието с гражданското общество – част 2,\" parliament.bg, Jan. 22, 2026. [Online]. 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These are some of the most common questions data engineers and architects wrestle with when starting a new Databricks initiative. This article gives you a practical, field-tested framework for scoping Databricks PoCs and MVPs so they survive the executive boardroom and make it to production.",[],{"_key":9734,"_type":99,"children":9735,"markDefs":9740,"style":170},"90eb6ad425c8",[9736],{"_key":9737,"_type":103,"marks":9738,"text":9739},"6b30502b6bd6",[],"TL;DR: How to Scope a Databricks PoC or MVP That Actually Gets Funded",[],{"_key":9742,"_type":99,"children":9743,"level":230,"listItem":231,"markDefs":9748,"style":107},"179d431c9596",[9744],{"_key":9745,"_type":103,"marks":9746,"text":9747},"e7cd0677a760",[],"80% of data projects fail before reaching production, almost always because they cannot prove return on investment, not because of technical issues.",[],{"_key":9750,"_type":99,"children":9751,"level":230,"listItem":231,"markDefs":9756,"style":107},"632ed1fe43ea",[9752],{"_key":9753,"_type":103,"marks":9754,"text":9755},"f0a35dd3431f",[],"Most teams no longer need a PoC. Databricks is a proven technology. What you need is an MVP that demonstrates business value.",[],{"_key":9758,"_type":99,"children":9759,"level":230,"listItem":231,"markDefs":9764,"style":107},"830cee7ec1da",[9760],{"_key":9761,"_type":103,"marks":9762,"text":9763},"9062a287b27b",[],"Use the 3-question framework to scope every project: (1) What value are we proving? (2) What technical risks are we validating? (3) What does success look like?",[],{"_key":9766,"_type":99,"children":9767,"level":230,"listItem":231,"markDefs":9772,"style":107},"852a32dc1bc7",[9768],{"_key":9769,"_type":103,"marks":9770,"text":9771},"b8480f8cd38c",[],"Always start with governance. In the AI age, well-governed data is a competitive advantage.",[],{"_key":9774,"_type":99,"children":9775,"level":230,"listItem":231,"markDefs":9780,"style":107},"befb8d980d98",[9776],{"_key":9777,"_type":103,"marks":9778,"text":9779},"59f86927e58f",[],"Get executive sign-off on your success criteria before you write a single line of code.",[],{"_key":9782,"_type":99,"children":9783,"level":230,"listItem":231,"markDefs":9788,"style":107},"42ba2034158a",[9784],{"_key":9785,"_type":103,"marks":9786,"text":9787},"8c1419664def",[],"Avoid the three project-killing mistakes: skipping CI/CD, rushing the timeline, and not securing upfront alignment.",[],{"_createdAt":9790,"_id":9791,"_key":9792,"_ref":9791,"_rev":9793,"_type":9794,"_updatedAt":9795,"afterTextLevel":170,"background":161,"bckg":161,"bigText":9796,"bigTextLevel":171,"button":9797,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"columns":9798,"content":161,"description":9799,"descriptionLevel":799,"image":161,"images":9847,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-17T09:49:48Z","d78cb333-8a94-4c4b-bd7e-ef3201c5161b","418415427cbb","2CyJ7ilKFCZjXFY9RU2ViI","imagesSection","2026-02-17T11:35:57Z","80% of Data Projects Fail: \nAnd It's Not the Technology",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},"2",[9800,9819,9831,9839],{"_key":9801,"_type":99,"children":9802,"markDefs":9816,"style":107},"d234333f63cc",[9803,9807,9812],{"_key":9804,"_type":103,"marks":9805,"text":9806},"cfe476fbec22",[],"The majority of data projects die before they ever reach production. ",{"_key":9808,"_type":103,"marks":9809,"text":9811},"6adec918432c",[9810],"ab10d3259bea","Research shows",{"_key":9813,"_type":103,"marks":9814,"text":9815},"ac30d318579d",[]," that roughly 80% of them fail, and the reason is almost never technical. The Spark jobs run fine. The Delta tables are set up properly. The data flows into the gold layer with minimal latency. The technology works.",[9817],{"_key":9810,"_type":173,"href":9818},"https://shieldbase.ai/blog/why-most-ai-pocs-fail-and-how-to-avoid-it",{"_key":9820,"_type":99,"children":9821,"markDefs":9830,"style":107},"4afa214cb8ea",[9822,9826],{"_key":9823,"_type":103,"marks":9824,"text":9825},"eca9a0120cb4",[],"What kills these projects is the inability to answer one question from the CFO: ",{"_key":9827,"_type":103,"marks":9828,"text":9829},"92c1238a1547",[3055],"how much money are we saving with this?",[],{"_key":9832,"_type":99,"children":9833,"markDefs":9838,"style":107},"42d4a893d2d5",[9834],{"_key":9835,"_type":103,"marks":9836,"text":9837},"769e49d30ac5",[],"We have seen this firsthand. For example, in a recent project, a team spent eight months building a Databricks MVP for a large enterprise. Everything was optimized properly, but when the team leader presented the results to the executive board, the CFO asked that one question and nobody had an answer. The CTO loved the technical output, but without a dollar figure, he did not have the ammunition to defend the project's budget. The team was dismantled. The project never continued.",[],{"_key":9840,"_type":99,"children":9841,"markDefs":9846,"style":107},"2c86aa9d36b2",[9842],{"_key":9843,"_type":103,"marks":9844,"text":9845},"ae9ed73b8468",[],"That story is not unique. It plays out in companies everywhere, and it is entirely preventable if you scope your PoC or MVP correctly from the start.",[],[9848],{"_key":9849,"_type":109,"alt":9850,"asset":9851},"81c6aa738e0a","Why data & AI projects fail - 5 reasons most AI PoCs never reach 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vs. MVP: Main Differences",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[9896,9904,9931,9958,9966],{"_key":9897,"_type":99,"children":9898,"markDefs":9903,"style":107},"64f34075554a",[9899],{"_key":9900,"_type":103,"marks":9901,"text":9902},"d9870a68899a",[],"A proof of concept and a minimum viable product answer fundamentally different questions, and confusing the two is one of the fastest ways to derail a project.",[],{"_key":9905,"_type":99,"children":9906,"level":230,"listItem":231,"markDefs":9928,"style":107},"608509fc1714",[9907,9911,9915,9919,9924],{"_key":9908,"_type":103,"marks":9909,"text":9910},"c59bae7af19a",[],"A ",{"_key":9912,"_type":103,"marks":9913,"text":9914},"63282b46ff75",[3055],"PoC answers: \"Can we build this?\"",{"_key":9916,"_type":103,"marks":9917,"text":9918},"278b29f88f2b",[]," It validates technical feasibility. 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Both approaches lead to the same place: a cancelled project.",[],{"_key":9967,"_type":99,"children":9968,"markDefs":9973,"style":107},"0b08a3ebf959",[9969],{"_key":9970,"_type":103,"marks":9971,"text":9972},"80a2445deb9f",[],"Here is the reality: in most cases today, you do not need a PoC. Databricks is already an established platform. It has proven itself across enterprise companies, startups, and widely different verticals. The stakeholders have already decided on the technology. What they need from you is proof that the project will deliver value. 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Every project has at least two types of stakeholders, and your MVP needs to satisfy both.",[],{"_key":10031,"_type":99,"children":10032,"level":230,"listItem":231,"markDefs":10041,"style":107},"557a0b3a3119",[10033,10037],{"_key":10034,"_type":103,"marks":10035,"text":10036},"9401e96ba8a2",[3055],"The budget holders",{"_key":10038,"_type":103,"marks":10039,"text":10040},"2a6192ed8544",[],": the CFO, the director, whoever approves funding. These people need to see value in terms they care about: faster compliance reports that reduce the risk of fines, removal of vendor lock-in that makes costs consumption-based and flexible, or dollar savings compared to the old system.",[],{"_key":10043,"_type":99,"children":10044,"level":230,"listItem":231,"markDefs":10053,"style":107},"8e6bbe4cd222",[10045,10049],{"_key":10046,"_type":103,"marks":10047,"text":10048},"c79cd9e4cce0",[3055],"The infrastructure owners",{"_key":10050,"_type":103,"marks":10051,"text":10052},"deec0a381f3f",[],": your DBAs, DevOps engineers, the people who will manage the solution day-to-day. They need to see that the new system is more stable, generates fewer support tickets, and reduces the chance of overloaded systems crashing under pressure.",[],{"_key":10055,"_type":99,"children":10056,"markDefs":10070,"style":799},"830dfc26787a",[10057,10061,10066],{"_key":10058,"_type":103,"marks":10059,"text":10060},"d62206ad7a02",[],"If you scope your MVP to address both audiences, your chances of getting to production with the next phase increase significantly. 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1: \nWhat Value Are We Proving?",[],{"_key":10144,"_type":99,"children":10145,"markDefs":10150,"style":799},"baca4d221f41",[10146],{"_key":10147,"_type":103,"marks":10148,"text":10149},"6879311e1db8",[],"Stop thinking about Spark performance and Delta table optimization for a moment. Answer this first: how much money is this project saving or generating for the company?",[],{"_key":10152,"_type":99,"children":10153,"markDefs":10166,"style":799},"69946fcc1f8e",[10154,10158,10162],{"_key":10155,"_type":103,"marks":10156,"text":10157},"e202d06b32a1",[],"Maybe you are cutting costs by replacing an expensive legacy system. Maybe faster reports mean the compliance team avoids regulatory fines. Maybe you are laying the data foundation for an AI strategy that makes the company more competitive. Whatever it is, you need to express it in dollars. ",{"_key":10159,"_type":103,"marks":10160,"text":10161},"4f72de9ad8b2",[3055],"If you cannot show financial value, the project stops here",{"_key":10163,"_type":103,"marks":10164,"text":10165},"7dc8f300342e",[],", and it should, because you would be building something nobody can justify funding.",[],{"_key":10168,"_type":99,"children":10169,"markDefs":10174,"style":171},"a700ec4db98a",[10170],{"_key":10171,"_type":103,"marks":10172,"text":10173},"6c006fae383d",[],"Question 2: \nWhat Technical Risks Are We Validating?",[],{"_key":10176,"_type":99,"children":10177,"markDefs":10182,"style":799},"9389deca97fe",[10178],{"_key":10179,"_type":103,"marks":10180,"text":10181},"8758904961f2",[],"The biggest mistake here is trying to validate everything at once. Do not scope an MVP that proves fifteen different technical capabilities. Pick one or two pieces that represent the highest risk and the greatest importance for your specific organization.",[],{"_key":10184,"_type":99,"children":10185,"markDefs":10202,"style":799},"6f211faf691d",[10186,10190,10194,10198],{"_key":10187,"_type":103,"marks":10188,"text":10189},"80f0489555a1",[],"Maybe it is compliance, and you need to demonstrate that ",{"_key":10191,"_type":103,"marks":10192,"text":8638},"9363eff4fdd7",[10193],"7754584d70fa",{"_key":10195,"_type":103,"marks":10196,"text":10197},"f37652cf7cc3",[]," is a significant improvement over your current governance setup. Maybe it is processing speed, and you need to show that Spark handles your workloads faster and more reliably. The specifics change from project to project, but the principle stays the same:",{"_key":10199,"_type":103,"marks":10200,"text":10201},"d50ddb04c6c0",[3055]," identify the riskiest technical assumption and make sure your MVP directly addresses it.",[10203],{"_key":10193,"_type":173,"href":10204},"https://www.databricks.com/product/unity-catalog",{"_key":10206,"_type":99,"children":10207,"markDefs":10212,"style":171},"65693cb781b9",[10208],{"_key":10209,"_type":103,"marks":10210,"text":10211},"b332acccda9f",[],"Question 3: \nWhat Specifically Does Success Look Like?",[],{"_key":10214,"_type":99,"children":10215,"markDefs":10220,"style":799},"13dac8ce74a7",[10216],{"_key":10217,"_type":103,"marks":10218,"text":10219},"37a921adfaa5",[],"This is where most teams get vague, and vague gets you defunded. Answers like \"we will migrate the data from the old system\" are not specific enough.",[],{"_key":10222,"_type":99,"children":10223,"markDefs":10228,"style":799},"6a7e2c67720c",[10224],{"_key":10225,"_type":103,"marks":10226,"text":10227},"eb0ba302bd17",[],"Specific looks like this: \"100% of streaming data is captured and available in the gold layer within five minutes of receipt.\"",[],{"_key":10230,"_type":99,"children":10231,"markDefs":10236,"style":799},"0b78721ef5aa",[10232],{"_key":10233,"_type":103,"marks":10234,"text":10235},"8cb3926b4a92",[],"When you define success in measurable, concrete terms and get those criteria signed off by the executive board before development starts, you create a contract. If you deliver on those terms, they have no reason to cut your funding. You will also find that specific criteria keep the team focused during development.",[],{"_key":10238,"_type":99,"children":10239,"markDefs":10244,"style":182},"73bad3defa87",[10240],{"_key":10241,"_type":103,"marks":10242,"text":10243},"0358b77ca5eb",[],"Why ROI Matters More Than Technical Brilliance",[],{"_key":10246,"_type":99,"children":10247,"markDefs":10252,"style":799},"5aab6973193d",[10248],{"_key":10249,"_type":103,"marks":10250,"text":10251},"eacf141cc618",[],"Engineers tend to think their Databricks Lakehouse is competing against the old SQL data warehouse. It is not, at least not in the executive's mind.",[],{"_key":10254,"_type":99,"children":10255,"markDefs":10260,"style":799},"e04261daf040",[10256],{"_key":10257,"_type":103,"marks":10258,"text":10259},"69aa4085f86a",[],"Your project is competing against every other project in the company. The marketing team is pitching a new content generation platform that will produce 100 more leads this quarter and bring in $50,000 in additional revenue. The R&D team wants a new development platform. Every department has a project they believe deserves the budget.",[],{"_key":10262,"_type":99,"children":10263,"markDefs":10277,"style":799},"420cf8a83449",[10264,10268,10273],{"_key":10265,"_type":103,"marks":10266,"text":10267},"7510e6dab291",[],"If the marketing team presents a clear dollar figure and your team presents \"we will migrate the data to the new system in a month,\" the CFO's choice is obvious. ",{"_key":10269,"_type":103,"marks":10270,"text":10272},"bae124515bbd",[10271],"337e2205fb9c","As this enterprise scoping guides point out",{"_key":10274,"_type":103,"marks":10275,"text":10276},"21f3d3c34367",[],", projects that fail to articulate ROI in the language of the business are consistently deprioritized regardless of their technical merit.",[10278],{"_key":10271,"_type":173,"href":10279},"https://beetroot.co/ai-ml/enterprise-guide-to-scoping-ai-mvps-balancing-risk-cost-speed/",{"_key":10281,"_type":99,"children":10282,"markDefs":10294,"style":799},"5d9879fe8ce4",[10283,10287,10291],{"_key":10284,"_type":103,"marks":10285,"text":10286},"65fd7f97834f",[],"Think in survival mode.",{"_key":10288,"_type":103,"marks":10289,"text":10290},"e877a2f6c46a",[3055]," If you do not put a price tag on what your project delivers, the project dies",{"_key":10292,"_type":103,"marks":10293,"text":793},"3c593cfd869c",[],[],{"_key":10296,"_type":99,"children":10297,"markDefs":10302,"style":182},"dc49981c236b",[10298],{"_key":10299,"_type":103,"marks":10300,"text":10301},"23e399627f4c",[],"Put Governance First! \nIt's Your Competitive Advantage",[],{"_key":10304,"_type":99,"children":10305,"markDefs":10310,"style":799},"64419875cb8d",[10306],{"_key":10307,"_type":103,"marks":10308,"text":10309},"8978ac132ba7",[],"Start with governance. Do not leave it for a later phase.",[],{"_key":10312,"_type":99,"children":10313,"markDefs":10327,"style":799},"8c12ab6ba5d8",[10314,10318,10323],{"_key":10315,"_type":103,"marks":10316,"text":10317},"3d913368a533",[],"The regulatory landscape has intensified. GDPR, DORA, and industry-specific requirements mean your company must demonstrate that data is protected, policies are enforced, and there are no leakages. For example, ",{"_key":10319,"_type":103,"marks":10320,"text":10322},"665f0708cf71",[10321],"bb095442b9bc","Databricks' own governance documentation",{"_key":10324,"_type":103,"marks":10325,"text":10326},"f15b8ad1b642",[]," makes clear that Unity Catalog is designed to be the foundation layer, not an afterthought.",[10328],{"_key":10321,"_type":173,"href":10329},"https://docs.databricks.com/aws/en/data-governance/",{"_key":10331,"_type":99,"children":10332,"markDefs":10353,"style":799},"62a84f4d0a75",[10333,10337,10341,10345,10350],{"_key":10334,"_type":103,"marks":10335,"text":10336},"24b552897347",[],"But governance is no longer just about compliance. In the AI age, it is a competitive advantage. Proper data descriptions, lineage tracking, and discoverability through ",{"_key":10338,"_type":103,"marks":10339,"text":8638},"788674df983c",[10340],"aeed9e9a4c57",{"_key":10342,"_type":103,"marks":10343,"text":10344},"96b2708ca23a",[]," mean that AI agents can navigate your data lake efficiently, surfacing context that would otherwise be impossible to find. Companies that govern their data well will move faster with AI than those sitting on an undocumented ",{"_key":10346,"_type":103,"marks":10347,"text":10349},"e18c24309388",[10348],"463771754d15","data swamp",{"_key":10351,"_type":103,"marks":10352,"text":793},"c0248928f615",[],[10354,10356],{"_key":10340,"_type":173,"href":10355},"https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/",{"_key":10348,"_type":173,"href":10357},"https://atlan.com/data-swamp-explained/",{"_key":10359,"_type":99,"children":10360,"markDefs":10365,"style":799},"2745290d423b",[10361],{"_key":10362,"_type":103,"marks":10363,"text":10364},"d4eba3e5c7a9",[],"Do not underestimate this. \nStart with governance from day one of your MVP, and you will set yourself apart.",[],{"_key":10367,"_type":99,"children":10368,"markDefs":10372,"style":799},"9eb1c2659468",[10369],{"_key":10370,"_type":103,"marks":10371,"text":4420},"01c264eec51a",[],[],{"_createdAt":10374,"_id":10375,"_key":10376,"_ref":10375,"_rev":10377,"_type":168,"_updatedAt":10378,"afterTextLevel":170,"background":161,"bckg":161,"bigText":10379,"bigTextLevel":171,"button":10380,"buttonPrimary":125,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":10381,"descriptionLevel":799,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-17T10:26:33Z","1c6688ff-3590-48bf-b441-53e025597e60","5d893e90c9a4","b26h2dVZZQ6kmNRGOHMO8p","2026-02-17T11:36:07Z","Three Mistakes That Kill \nDatabricks Projects",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[10382,10390,10431,10439,10447,10455],{"_key":10383,"_type":99,"children":10384,"markDefs":10389,"style":171},"d337c59f7123",[10385],{"_key":10386,"_type":103,"marks":10387,"text":10388},"3f7f14608db3",[],"Mistake 1: \nSkipping Version Control and CI/CD",[],{"_key":10391,"_type":99,"children":10392,"markDefs":10424,"style":799},"b97ef9fca241",[10393,10397,10402,10406,10411,10415,10420],{"_key":10394,"_type":103,"marks":10395,"text":10396},"ab78f05bf860",[],"Your MVP is not a throwaway prototype. In most cases, it becomes the foundation of the production system. If that foundation has no version control, no CI/CD pipeline, and no use of ",{"_key":10398,"_type":103,"marks":10399,"text":10401},"328609bd08a1",[10400],"410e7732705c","Databricks Asset Bundles",{"_key":10403,"_type":103,"marks":10404,"text":10405},"2d5207e0a67e",[],", you are building ",{"_key":10407,"_type":103,"marks":10408,"text":10410},"961cab8852b3",[10409],"a43059135edc","technical debt",{"_key":10412,"_type":103,"marks":10413,"text":10414},"d1b2364e3928",[]," into the project from the start. Follow ",{"_key":10416,"_type":103,"marks":10417,"text":10419},"02e1c0163ebd",[10418],"d72decaf37fb","operational best practices",{"_key":10421,"_type":103,"marks":10422,"text":10423},"af7f85dac5a5",[]," from day one. It costs less time now than fixing it later.",[10425,10427,10429],{"_key":10400,"_type":173,"href":10426},"https://docs.databricks.com/aws/en/dev-tools/bundles/templates",{"_key":10409,"_type":173,"href":10428},"https://www.confluent.io/learn/tech-debt/",{"_key":10418,"_type":173,"href":10430},"https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/operational-excellence/best-practices",{"_key":10432,"_type":99,"children":10433,"markDefs":10438,"style":171},"77ae2e2fffaf",[10434],{"_key":10435,"_type":103,"marks":10436,"text":10437},"0e46bd3f2bc2",[],"Mistake 2: \nNot Giving Your MVP Enough Time",[],{"_key":10440,"_type":99,"children":10441,"markDefs":10446,"style":799},"3ba984a90395",[10442],{"_key":10443,"_type":103,"marks":10444,"text":10445},"06396d125a49",[],"MVPs are not quick-and-dirty technical demos. You need six to eight weeks to cover enough scope to demonstrate real value. Rushing the timeline means cutting corners on the exact things that prove ROI to the business. Build it properly or do not build it at all.",[],{"_key":10448,"_type":99,"children":10449,"markDefs":10454,"style":171},"947f9928f048",[10450],{"_key":10451,"_type":103,"marks":10452,"text":10453},"50cdccb291bd",[],"Mistake 3: \nNot Getting Executive Sign-Off Upfront",[],{"_key":10456,"_type":99,"children":10457,"markDefs":10462,"style":799},"78f203d97ef0",[10458],{"_key":10459,"_type":103,"marks":10460,"text":10461},"6fb33bba47e9",[],"When you answer Question 3 with specific success criteria, take them to the executive board and get them approved before development begins. This is your insurance policy. If the leadership agreed to those targets at the start, they cannot reasonably pull funding when you deliver on them. Without this sign-off, you are building on hope instead of commitment.",[],{"_createdAt":10464,"_id":10465,"_key":10466,"_ref":10465,"_rev":10467,"_type":10468,"_updatedAt":10469,"background":161,"bckg":161,"bigText":10470,"bigTextLevel":171,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":161,"description":10471,"descriptionLevel":799,"image":161,"images":161,"links":10488,"panelTitle":10542,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-02-17T10:19:56Z","20ff1d3c-f278-420e-ac3c-d1f14c47200d","ecf5c8f71423","b26h2dVZZQ6kmNRGOHMPdZ","nextUpSection","2026-02-17T11:36:09Z","What to Do Next",[10472,10480],{"_key":10473,"_type":99,"children":10474,"markDefs":10479,"style":107},"9e6412ec238b",[10475],{"_key":10476,"_type":103,"marks":10477,"text":10478},"99742e391ff8",[],"This framework is the same one we walk through in detail, with real examples and a full breakdown, in our video on Databricks PoC and MVP scoping, which you can watch on our YouTube channel.",[],{"_key":10481,"_type":99,"children":10482,"markDefs":10487,"style":107},"1015863a920e",[10483],{"_key":10484,"_type":103,"marks":10485,"text":10486},"880f53b21d29",[],"If you want to apply this to your own project right now, we have put together a free PDF checklist that turns the 3-question framework into a step-by-step worksheet you can fill in with your team. 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They’re the ones who understand what those features enable competitively.",[],{"_key":11508,"_type":99,"children":11509,"markDefs":11522,"style":799},"evx-K2AutVnbZWwG26HXZ",[11510,11514,11518],{"_key":11511,"_type":103,"marks":11512,"text":11513},"4b0e730bebbd",[],"What’s your organization’s approach to evaluating ",{"_key":11515,"_type":103,"marks":11516,"text":11517},"6082097f1f47",[3055],"data lakehouse platform",{"_key":11519,"_type":103,"marks":11520,"text":11521},"7b31b2c282cd",[]," updates for strategic advantage?",[],{"_key":11524,"_type":99,"children":11525,"markDefs":11529,"style":107},"a8bcafd1fe07",[11526],{"_key":11527,"_type":103,"marks":11528,"text":4420},"09c4b152c985",[],[],{"_key":11531,"_type":99,"children":11532,"markDefs":11537,"style":107},"f6d33db6e283",[11533],{"_key":11534,"_type":103,"marks":11535,"text":11536},"ff4e2053b10a",[],"Cosmos Thrace is a Databricks consulting partner specializing in Lakehouse architecture, Unity Catalog, and AI/ML implementations across Europe. 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You’d click purchase, watch the progress bar crawl forward, and hope your internet connection didn’t drop mid-download. Only after the entire file landed on your hard drive could you actually hear if it was the right track. That friction between intent and validation defined the iTunes era.",[],{"_key":11628,"_type":99,"children":11629,"markDefs":11634,"style":799},"M7GPuYZTAp9YRNHZuvF18",[11630],{"_key":11631,"_type":103,"marks":11632,"text":11633},"6d04125ba540",[],"Then Spotify arrived. Instant playback. No downloads. No waiting. The shift wasn’t just about convenience; it fundamentally changed how people discovered, consumed, and thought about music.",[],{"_key":11636,"_type":99,"children":11637,"markDefs":11642,"style":799},"X5H-3i5jANmXihSGyM5gD",[11638],{"_key":11639,"_type":103,"marks":11640,"text":11641},"241ef6fc8139",[],"We’ve watched data engineering teams operate in their own “iTunes era” for years, even on modern lakehouse platforms. Engineers write pipeline logic in Databricks notebooks, configure Delta Live Tables orchestration, wait for full execution cycles, and only then discover if their transformation logic works correctly. A single syntax error discovered after a 45-minute pipeline run compounds across every iteration, multiplying time-to-insight and delaying the business decisions waiting downstream.",[],{"_key":11644,"_type":99,"children":11645,"markDefs":11650,"style":799},"dOXyKk5TrGpPdPtJG5uxy",[11646],{"_key":11647,"_type":103,"marks":11648,"text":11649},"a2b7629b8f7e",[],"Databricks just delivered their Spotify moment. And did it with a bang!",[],{"_key":11652,"_type":99,"children":11653,"markDefs":11658,"style":182},"zmGKeG6zX_AsO6XmZ9sLK",[11654],{"_key":11655,"_type":103,"marks":11656,"text":11657},"eb7c2a9fe767",[],"From Sequential Deploys to Continuous Validation",[],{"_key":11660,"_type":99,"children":11661,"markDefs":11666,"style":799},"4vXyj2HCX7Zqt1SVb8OVR",[11662],{"_key":11663,"_type":103,"marks":11664,"text":11665},"7eca401698fc",[],"In traditional Databricks pipeline development, validation happens at the end. You write SQL transformations in notebooks, configure Delta Live Tables orchestration logic, deploy the entire pipeline to a development workspace, trigger a run, and wait. If something breaks (a join condition that doesn’t account for Unity Catalog’s data governance rules, a data quality expectation that’s too restrictive, a dependency that wasn’t properly sequenced), you discover it only after full execution completes against your Delta tables.",[],{"_key":11668,"_type":99,"children":11669,"markDefs":11674,"style":799},"I5KqehGWNJivV4WlhIonH",[11670],{"_key":11671,"_type":103,"marks":11672,"text":11673},"e0d4ea4970ba",[],"Every iteration cycle that takes hours instead of seconds doesn’t just delay one engineer. It cascades. Downstream teams wait for validated Delta tables. Analytics projects built on Databricks SQL stall. Machine learning engineers can’t access the feature tables they need for model training in MLflow. Business stakeholders make decisions with stale dashboards.",[],{"_key":11676,"_type":99,"children":11677,"markDefs":11682,"style":799},"bLtuOOwd4-FE4DUrOhUqz",[11678],{"_key":11679,"_type":103,"marks":11680,"text":11681},"30559f3bd71d",[],"The new IDE for Data Engineering fundamentally changes this equation. Built directly into the Databricks workspace for Lakeflow Spark Declarative Pipelines, it provides instant execution feedback as you declare your datasets. You write a transformation that creates a new Delta table, and the IDE immediately validates your syntax, shows you the dependency graph, and lets you execute just that specific dataset to preview results. A misconfigured join to a Unity Catalog table gets caught in seconds.",[],{"_key":11684,"_type":99,"children":11685,"markDefs":11690,"style":799},"E17ZtIeHPvMx8LuYvm7zV",[11686],{"_key":11687,"_type":103,"marks":11688,"text":11689},"b7d287ad0af9",[],"We’ve observed enterprises reduce Databricks pipeline development time by 60-70% when they adopt the IDE. You declare your desired state (what Delta tables should exist, what quality expectations must hold) and the IDE continuously validates that logic as you write it. When your team can test and validate pipeline logic in minutes instead of hours, you compress the entire cycle from data request to business insight on the lakehouse platform.",[],{"_key":11692,"_type":99,"children":11693,"markDefs":11698,"style":182},"CUQJ5rx7OYWpsLv_7GYxN",[11694],{"_key":11695,"_type":103,"marks":11696,"text":11697},"48a93998e441",[],"Unified Development Surface Eliminates Context Switching",[],{"_key":11700,"_type":99,"children":11701,"markDefs":11706,"style":799},"tvlLxNTKhK1TPrn5J36Ji",[11702],{"_key":11703,"_type":103,"marks":11704,"text":11705},"56336e1833d7",[],"Here’s the pre-IDE workflow in practice: Your data engineer opens a Databricks notebook to write transformation logic. They switch to the Delta Live Tables UI to configure the pipeline DAG. They navigate to the Jobs tab to check if the last scheduled run completed. They open another browser tab to query Delta tables in the Data Explorer. They context-switch to Repos to commit changes to Git. They move back to pipeline configuration to adjust compute clusters. Each transition creates cognitive overhead that accumulates across dozens of daily iterations.",[],{"_key":11708,"_type":99,"children":11709,"markDefs":11714,"style":799},"27qNDe6qGIAdpc6sUcwdG",[11710],{"_key":11711,"_type":103,"marks":11712,"text":11713},"1df1a24e052d",[],"The Databricks IDE for Data Engineering collapses this fragmentation. Code, the automatically-generated dependency graph of your Delta tables, results preview with data profiling, Unity Catalog schema references, quality expectation configuration, and debugging tools exist in a unified surface. Engineers see their pipeline’s DAG update in real-time as they declare new datasets. They preview Delta table outputs directly alongside the transformation logic that generates them. They configure Lakeflow Jobs scheduling without leaving the IDE. Git integration through Databricks Repos happens inline.",[],{"_key":11716,"_type":99,"children":11717,"markDefs":11722,"style":799},"Fzdxrs8f8v2yIXr40oheO",[11718],{"_key":11719,"_type":103,"marks":11720,"text":11721},"1cd77c53ef2b",[],"When you eliminate the overhead of switching between six different Databricks workspace surfaces just to validate a single Delta Live Tables change, you fundamentally change organizational velocity. Teams that operate in the unified IDE consistently deliver production pipelines to Delta Lake 40-50% faster than teams working across fragmented Databricks notebook workflows.",[],{"_key":11724,"_type":99,"children":11725,"markDefs":11730,"style":182},"FWGW7Ije5_Q1itGid2hi1",[11726],{"_key":11727,"_type":103,"marks":11728,"text":11729},"c73a3fc072cf",[],"Selective Execution Transforms Iteration Speed",[],{"_key":11732,"_type":99,"children":11733,"markDefs":11738,"style":799},"bTOtSBkgYsGYjjxCp3Yo0",[11734],{"_key":11735,"_type":103,"marks":11736,"text":11737},"f26c72d5b982",[],"Traditional Delta Live Tables orchestration operates on an all-or-nothing premise. When you modify transformation logic in one part of your pipeline, you typically redeploy and rerun the entire workflow. The IDE for Data Engineering enables selective execution of individual datasets and their dependencies. Engineers modify a single transformation that creates a specific Delta table, click to rerun just that dataset and its downstream dependencies, and validate the change in seconds while the rest of the pipeline continues operating normally.",[],{"_key":11740,"_type":99,"children":11741,"markDefs":11746,"style":799},"1f4T2BhfDQzINvmyl3HnY",[11742],{"_key":11743,"_type":103,"marks":11744,"text":11745},"8df8abd26419",[],"Consider fixing a data quality issue in a production Delta table. In the notebook-based approach, you identify the problem, modify the logic, redeploy the full Delta Live Tables pipeline, wait for complete re-execution across all your Delta tables, and hope nothing else broke. That cycle might take hours and consume significant Databricks compute resources. In the IDE, you modify the specific transformation with the quality expectation issue, rerun just that dataset and its dependencies, validate the fix in minutes with minimal compute cost, and push the change to production.",[],{"_key":11748,"_type":99,"children":11749,"markDefs":11754,"style":799},"DYAB8ah-Hn5wFVpG4ee8s",[11750],{"_key":11751,"_type":103,"marks":11752,"text":11753},"deb6251fd761",[],"Enterprises we work with routinely manage Databricks pipelines with hundreds of individual Delta table transformations, all governed by Unity Catalog, serving dozens of downstream Databricks SQL analytics and MLflow model training applications. The ability to iterate on specific datasets without triggering full pipeline reruns is the difference between a data platform that enables rapid experimentation and one that becomes an organizational bottleneck.",[],{"_key":11756,"_type":99,"children":11757,"markDefs":11762,"style":182},"9pVejKhKNhpsFNXBoNPo5",[11758],{"_key":11759,"_type":103,"marks":11760,"text":11761},"fa2b5d912d16",[],"The Strategic Question",[],{"_key":11764,"_type":99,"children":11765,"markDefs":11770,"style":799},"o5Mj1keYe0ZtjwU5tgypl",[11766],{"_key":11767,"_type":103,"marks":11768,"text":11769},"952bfb47bc5e",[],"The technology shift from notebook-based to IDE-native pipeline development in Databricks isn’t coming. It’s already here. The IDE for Data Engineering launched in Public Preview and represents Databricks’ opinionated direction for how declarative pipelines should be built on the lakehouse platform.",[],{"_key":11772,"_type":99,"children":11773,"markDefs":11778,"style":799},"I79hXeKUAcE2qG1IBdXCB",[11774],{"_key":11775,"_type":103,"marks":11776,"text":11777},"2dce1b648fe0",[],"Your organization will make this transition eventually. The question facing data leaders today isn’t whether to modernize Databricks pipeline development workflows. It’s whether you’ll lead that modernization proactively (capturing the competitive advantage from higher engineering velocity on the lakehouse) or whether you’ll adopt it reactively, after watching competitors iterate faster on their Delta Lake data products quarter after quarter.",[],{"_key":11780,"_type":99,"children":11781,"markDefs":11786,"style":799},"PGS_uJ5sDhQBQ0kBoabGh",[11782],{"_key":11783,"_type":103,"marks":11784,"text":11785},"84ccbe5858c4",[],"Consider your current state: How many hours per week does your Databricks data engineering team spend waiting for Delta Live Tables pipeline validation? How many potential experiments with Unity Catalog data models never happen because the notebook-based iteration cost is too high? How many business opportunities arrive and depart while your team works through deployment cycles that should take minutes in the IDE but stretch into days?",[],{"_key":11788,"_type":99,"children":11789,"markDefs":11794,"style":799},"EHCk7pa-E8-SWjYimPZZF",[11790],{"_key":11791,"_type":103,"marks":11792,"text":11793},"d7b92eeedc2f",[],"The music industry didn’t go back to iTunes after experiencing Spotify. Your Databricks data engineering team won’t go back to notebook-based development after experiencing the IDE’s continuous validation.",[],{"_key":11796,"_type":99,"children":11797,"markDefs":11802,"style":107},"d4ae8ec14d5a",[11798],{"_key":11799,"_type":103,"marks":11800,"text":11801},"1f0683d3e29f",[],"Cosmos Thrace is a Databricks consulting partner specializing in Lakehouse architecture, Unity Catalog, and AI/ML implementations across Europe.",[],{"_type":17,"current":11607},[11805,11806],{"_createdAt":10726,"_id":10727,"_rev":10728,"_type":8636,"_updatedAt":10729,"name":14,"orderRank":10730,"uid":18},{"_createdAt":11807,"_id":11808,"_rev":11809,"_type":8636,"_updatedAt":11810,"name":11811,"orderRank":11812,"uid":11813},"2026-01-20T12:27:46Z","8a2eff5c-1fca-4d1e-9563-f6cd54a56108","1XrksDlMkoAPinyrcu4kWR","2026-01-20T12:27:51Z","Data Engineer","0|1000c8:","data-engineer",{"_createdAt":11815,"_id":11816,"_rev":11817,"_system":11818,"_type":72,"_updatedAt":11821,"author":161,"category":11822,"date":11826,"description":11827,"image":11836,"name":11870,"oldSlug":11871,"orderRank":11872,"reviewer":161,"sections":11873,"seo":161,"slug":12139,"tags":12140},"2026-01-15T15:36:42Z","60734bd4-002d-4ef6-8947-55a1bcfacf3e","88krvpD0WevGUmtRGQ8QFc",{"base":11819},{"id":11816,"rev":11820},"2oGVswEwQBfyYUvi7k0gJx","2026-01-30T13:13:01Z",{"_createdAt":6,"_id":7,"_rev":8,"_system":11823,"_type":12,"_updatedAt":13,"name":14,"orderRank":15,"slug":11825,"uid":18},{"base":11824},{"id":7,"rev":11},{"_type":17,"current":18},"2025-11-28",[11828],{"_key":11829,"_type":99,"children":11830,"markDefs":11835,"style":107},"7d69d604f91c",[11831],{"_key":11832,"_type":103,"marks":11833,"text":11834},"943776398093",[],"Enterprise finance teams face a paradox. 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They’re expected to deliver faster closes, provide real-time visibility into revenue performance, and guide strategic decisions with data-driven insights. Yet according to industry research, organizations spend 30 to 40% of their finance team’s time on manual reconciliation tasks. A ",{"_key":11891,"_type":103,"marks":11892,"text":11894},"22b33787ee64",[11893],"bTTgwcsqzZ2O1LbOKRt2i","2023 Gartner survey",{"_key":11896,"_type":103,"marks":11897,"text":11898},"625b1773cee1",[]," of nearly 500 accounting professionals revealed that 18% make financial errors daily, with mounting workload pressure cited as the primary driver.",[11900],{"_key":11893,"_type":173,"href":11901},"https://www.nominal.so/blog/automated-reconciliation",{"_key":11903,"_type":99,"children":11904,"markDefs":11909,"style":799},"aT65cmrXkxstGf0jZv2VY",[11905],{"_key":11906,"_type":103,"marks":11907,"text":11908},"99098aaef357",[],"This isn’t a staffing problem. It’s an architectural one.",[],{"_key":11911,"_type":99,"children":11912,"markDefs":11917,"style":799},"PqRRbmxtAX3BF7jC-58OS",[11913],{"_key":11914,"_type":103,"marks":11915,"text":11916},"aee723d3ae60",[],"The organizations we work with describe the same pattern: time tracking systems capture operational reality, billing rates live in spreadsheets with fragmented version control, contract terms exist in disconnected repositories, and someone must manually reconcile everything to calculate revenue. Senior financial analysts spend their last week of each month in what one CFO described as “spreadsheet gymnastics,” validating calculations that should happen automatically.",[],{"_key":11919,"_type":99,"children":11920,"markDefs":11925,"style":799},"TGI-bPaGmDPMtKDloBPuA",[11921],{"_key":11922,"_type":103,"marks":11923,"text":11924},"678bd985a0f4",[],"The cost transcends wasted hours. When finance teams receive revenue updates two weeks after month-end, strategic opportunities have already passed. When billing disputes arise from manual calculation errors, client relationships suffer. When leadership questions whether financial numbers are final, organizational trust erodes. Manual revenue recognition isn’t just operationally inefficient. It’s a competitive liability in markets where decision velocity determines winners.",[],{"_key":11927,"_type":99,"children":11928,"markDefs":11933,"style":799},"tFKqFwxeObgW5vQIHi5H8",[11929],{"_key":11930,"_type":103,"marks":11931,"text":11932},"395b55a0e463",[],"The enterprises breaking through this constraint aren’t hiring more analysts or working longer hours. They’re eliminating the constraint through an automation architecture that converts reconciliation work into strategic capacity. So how do leading enterprises address this?",[],{"_key":11935,"_type":99,"children":11936,"markDefs":11941,"style":182},"oPOZTeFfWvVE0RBVRMDIc",[11937],{"_key":11938,"_type":103,"marks":11939,"text":11940},"33ef77e83761",[],"The Strategic Architecture of Automated Revenue Recognition",[],{"_key":11943,"_type":99,"children":11944,"markDefs":11949,"style":799},"0t4aJn5RIgyoZQ74V1_uL",[11945],{"_key":11946,"_type":103,"marks":11947,"text":11948},"b47f45ec0d50",[],"The transformation begins with a fundamental shift in how enterprises architect their financial data foundation. Traditional approaches treat revenue calculation as a monthly event requiring heroic effort from finance teams. Modern approaches recognize that revenue recognition is a continuous process that should execute automatically as operational data flows through the organization.",[],{"_key":11951,"_type":99,"children":11952,"markDefs":11957,"style":799},"oB8ldTOnGx1lE8xl2NK_W",[11953],{"_key":11954,"_type":103,"marks":11955,"text":11956},"07b35380d6b6",[],"Professional services firms, consulting organizations, and project-based businesses face particular complexity in revenue recognition. Billable hours tracked in time management systems must be matched with billing rates that vary by client, engagement, and role. Contract terms specify caps, milestones, and recognition timing. Project codes connect activity to revenue streams. Historically, finance teams manually knit these elements together each month.",[],{"_key":11959,"_type":99,"children":11960,"markDefs":11965,"style":799},"Yp6Kmyt-LJCGAauaUcryo",[11961],{"_key":11962,"_type":103,"marks":11963,"text":11964},"abb322532dd5",[],"The architectural solution consolidates these disconnected elements into a unified data foundation. Time entries flow automatically from operational systems into governed data lakehouse tables through API-based ingestion. Rate structures move from spreadsheet files into structured, versioned data tables with clear ownership and audit trails. Validation logic that previously lived in analyst institutional knowledge becomes codified business rules that execute continuously. Revenue calculations happen automatically as new data arrives, not on demand when finance teams request reports.",[],{"_key":11967,"_type":99,"children":11968,"markDefs":11986,"style":799},"Np5S7MXrI3l7Tsfdl_b1t",[11969,11974,11978,11982],{"_key":11970,"_type":103,"marks":11971,"text":11973},"1b95792ee460",[11972],"1Rj9kyfm4y6eJME_pAYZD","Mahindra & Mahindra",{"_key":11975,"_type":103,"marks":11976,"text":11977},"31f412ff4f3f",[]," demonstrated this principle at enterprise scale. They developed a GenAI bot for financial analysts on the Databricks platform that led to a",{"_key":11979,"_type":103,"marks":11980,"text":11981},"3c557915581a",[3055]," 70% reduction",{"_key":11983,"_type":103,"marks":11984,"text":11985},"e1e2fab40c8d",[]," in time spent on routine tasks, enabling teams to focus on higher-value strategic initiatives. The transformation wasn’t about making spreadsheets faster. It was about eliminating spreadsheets from the critical path of financial insight.",[11987],{"_key":11972,"_type":173,"href":11988},"https://www.databricks.com/blog/data-ai-use-cases-worlds-leading-companies",{"_key":11990,"_type":99,"children":11991,"markDefs":11996,"style":799},"AJuieKZ3VRmxHLOA1sc3r",[11992],{"_key":11993,"_type":103,"marks":11994,"text":11995},"a5dd57091e6d",[],"Consider the contrast with legacy approaches. Traditional financial operations treat each month-end as an isolated event. Analysts extract data from time tracking systems, match it against rate sheets, validate contract compliance, calculate revenue, and prepare reports. The workflow is sequential and manual. If an analyst leaves mid-month, institutional knowledge walks out with them. Automated architectures flip this model. Workflows execute on schedule, not on request. Business logic lives in version-controlled code, not in spreadsheet formulas scattered across shared drives.",[],{"_key":11998,"_type":99,"children":11999,"markDefs":12004,"style":182},"gpLoQSxoEngvv9341_i-b",[12000],{"_key":12001,"_type":103,"marks":12002,"text":12003},"cb73aad5e548",[],"From Data Silos to Strategic Capacity",[],{"_key":12006,"_type":99,"children":12007,"markDefs":12012,"style":799},"uzllo29B3_88q36zwQElc",[12008],{"_key":12009,"_type":103,"marks":12010,"text":12011},"62fd984d7368",[],"The second strategic element addresses what happens when automation frees finance teams from reconciliation work. We implemented this approach for a professional services organization with revenue spread across 200+ client engagements. Their finance team pulled time data from Clockify, cross-referenced rates in Google Sheets maintained by practice leads, validated against project codes in their CRM, then manually calculated billable revenue. The process consumed 40+ hours monthly. Errors were inevitable. Leadership received financial visibility two weeks after close.",[],{"_key":12014,"_type":99,"children":12015,"markDefs":12020,"style":799},"87eQs6tGNhY183qDBdUwP",[12016],{"_key":12017,"_type":103,"marks":12018,"text":12019},"921a66237627",[],"The transformation architecture consolidated these disparate elements into Delta Lake as the unified foundation. Bronze layer tables ingest raw time entries from Clockify API with complete historical fidelity. Silver layer workflows enrich time data with billing rates from structured rate tables, replacing spreadsheet lookups with governed data access. Automated validation logic flags discrepancies between logged hours and contract terms immediately, not at month-end. Gold layer aggregations calculate revenue by client, project, and practice area with full audit trails showing exactly how every number derived.",[],{"_key":12022,"_type":99,"children":12023,"markDefs":12028,"style":799},"SrMpIlwuO1DnQXXoWYk7k",[12024],{"_key":12025,"_type":103,"marks":12026,"text":12027},"458b3cbda08d",[],"The impact extended beyond efficiency. Month-end reconciliation dropped from 40 hours to zero. Finance redeployed from data validation to margin analysis, discovering underutilized capacity worth significant annual revenue. Leadership shifted from monthly financial reviews to daily revenue dashboard checks. Billing accuracy improved measurably, reducing client disputes.",[],{"_key":12030,"_type":99,"children":12031,"markDefs":12036,"style":799},"XPA0Yd8y5AxAO3N6GKZIC",[12032],{"_key":12033,"_type":103,"marks":12034,"text":12035},"14c85396a692",[],"Block achieved similar outcomes at greater scale. Using Databricks, they realized a 12x reduction in computing costs while redefining financial services infrastructure for real-time payment processing and revenue recognition across their global platform.",[],{"_key":12038,"_type":99,"children":12039,"markDefs":12044,"style":799},"Dzl0rexEOC802cPQ_N3kp",[12040],{"_key":12041,"_type":103,"marks":12042,"text":12043},"37e8b51b591f",[],"The critical difference from legacy architectures is governance embedded in the platform rather than enforced through process. Unity Catalog provides fine-grained access control across the data lakehouse. Finance sees revenue calculations. Operations sees project metrics. Leadership sees aggregated performance. All querying identical gold tables, ensuring consistency. Data lineage is automatic, not reconstructed manually during audits",[],{"_key":12046,"_type":99,"children":12047,"markDefs":12052,"style":182},"UISR4UEGwWEaFxnccM-sJ",[12048],{"_key":12049,"_type":103,"marks":12050,"text":12051},"ddc8453d3d9e",[],"The Implementation Framework",[],{"_key":12054,"_type":99,"children":12055,"markDefs":12060,"style":799},"9O4xZH7irgWXZw9MR5xEd",[12056],{"_key":12057,"_type":103,"marks":12058,"text":12059},"9f2ff806092b",[],"Enterprises considering this transformation consistently ask about implementation complexity and organizational change management. Revenue recognition offers ideal characteristics for automation: repetitive monthly workflows, clear business logic, measurable outcomes, and high organizational visibility. Success here builds credibility for broader financial automation initiatives.",[],{"_key":12062,"_type":99,"children":12063,"markDefs":12068,"style":799},"qSbool6cM-RHmpgg0fuDx",[12064],{"_key":12065,"_type":103,"marks":12066,"text":12067},"103cebdd9e57",[],"The technical pattern follows medallion architecture principles. Bronze layer ingests operational data from source systems with API connectivity where available and batch extraction where necessary. Silver layer applies business rules, validation logic, and enrichment workflows to transform raw data into business entities. Gold layer aggregates data into analytical structures optimized for executive consumption. Scheduled workflows execute transformations automatically, eliminating manual intervention.",[],{"_key":12070,"_type":99,"children":12071,"markDefs":12076,"style":799},"q_U4iAuLbZVB-Mcf0tc3U",[12072],{"_key":12073,"_type":103,"marks":12074,"text":12075},"f52b94d02026",[],"The organizational pattern requires finance leadership to shift from hands-on calculation to workflow oversight. Instead of validating every revenue calculation manually, finance teams define business rules that validate calculations automatically. Exceptions surface for review, not entire datasets. This transition from “check everything” to “manage exceptions” requires trust in the platform and clarity in business logic codification.",[],{"_key":12078,"_type":99,"children":12079,"markDefs":12084,"style":799},"g6nrGkM6KwPhjYiqzsecQ",[12080],{"_key":12081,"_type":103,"marks":12082,"text":12083},"66ce70c3b6cf",[],"Unity Catalog provides the governance foundation. Define data domains with clear ownership. Implement access controls that reflect organizational hierarchy. Establish audit trails for all transformations. Create data quality metrics that surface automatically. Treat data governance as architectural requirement, not operational afterthought.",[],{"_key":12086,"_type":99,"children":12087,"markDefs":12091,"style":182},"tuldvRn-TeqrwKA47OwLk",[12088],{"_key":12089,"_type":103,"marks":12090,"text":4733},"9dc5c664bcb2",[],[],{"_key":12093,"_type":99,"children":12094,"markDefs":12099,"style":799},"nTiFzDyIKYt2BcJ8fpaKF",[12095],{"_key":12096,"_type":103,"marks":12097,"text":12098},"9b5d847bb2e7",[],"Enterprise finance automation represents more than operational improvement. It’s a strategic imperative for organizations competing in markets where decision velocity determines winners. When finance teams spend 30 to 40% of their time on manual reconciliation, they’re not available for strategic work that drives competitive advantage.",[],{"_key":12101,"_type":99,"children":12102,"markDefs":12107,"style":799},"w_yMZv8cOItKMLxA7YZoD",[12103],{"_key":12104,"_type":103,"marks":12105,"text":12106},"8a0ffa986a94",[],"The transformation from manual reconciliation to automated revenue recognition follows clear architectural principles. Consolidate disconnected data sources into unified lakehouse foundations. Codify business logic that currently lives in spreadsheets and institutional knowledge. Build continuous workflows that execute automatically rather than manual processes that happen monthly. Embed governance in platform architecture rather than enforcing it through process overhead.",[],{"_key":12109,"_type":99,"children":12110,"markDefs":12115,"style":799},"bu4Y7Udqjfly_mMBnq5K8",[12111],{"_key":12112,"_type":103,"marks":12113,"text":12114},"2bc8ab66e0d5",[],"The enterprises leading this transformation don’t view automation as replacing finance teams. They recognize automation as redirecting finance talent from mechanical validation to strategic insight. When analysts stop reconciling spreadsheets, they start identifying margin opportunities, pricing inefficiencies, and capacity utilization gaps that drive real business value.",[],{"_key":12117,"_type":99,"children":12118,"markDefs":12123,"style":799},"MCdSEy8HhhF1UkPqz321v",[12119],{"_key":12120,"_type":103,"marks":12121,"text":12122},"68a1b804f940",[],"The competitive gap between organizations with real-time financial intelligence and those waiting weeks for month-end reports will only widen. Markets reward velocity. Automation enables velocity. The strategic question facing enterprise finance leaders isn’t whether to automate revenue recognition. It’s whether they can afford the competitive disadvantage of continuing manual processes while competitors automate.",[],{"_key":12125,"_type":99,"children":12126,"markDefs":12131,"style":799},"CP7ajm6x73GLyq66buYTk",[12127],{"_key":12128,"_type":103,"marks":12129,"text":12130},"a9f1db54a562",[],"What percentage of your finance team’s strategic capacity is currently locked in spreadsheet reconciliation? And what competitive opportunities could that capacity unlock if redirected to strategic work? 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Permission Bottlenecks to Scaling Data Governance: The Shift to Attribute-Based Access Control","from-permission-bottlenecks-to-scaling-data-governance-the-shift-to-attribute-based-access-control","0|10007c:",[12217],{"_createdAt":12218,"_id":12219,"_key":12220,"_ref":12219,"_rev":12221,"_system":12222,"_type":168,"_updatedAt":12225,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":12226,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:23:59Z","lv2ScyYYFNvMF2HGLexex","jG7FlsQh0ZebC_-RJBh7f","3x1HJiv3wwU7cYVoHsYJPz",{"base":12223},{"id":12219,"rev":12224},"7hw4Cb1llohacCi9MHZOqZ","2026-01-28T07:36:09Z",[12227,12235,12254,12262,12281,12289,12297,12305,12313,12321,12329,12337,12345,12363,12371,12379,12387,12395,12403,12422,12430,12438,12446,12454,12462,12470,12478,12486,12494,12502,12510,12528,12536,12544],{"_key":12228,"_type":99,"children":12229,"markDefs":12234,"style":799},"kOiqswu0u-bZcam0pSZ7O",[12230],{"_key":12231,"_type":103,"marks":12232,"text":12233},"4a31682a93bb",[],"We’ve watched too many enterprise data initiatives stall not because of technology limitations, but because of a governance paradox: the more successful you become at democratizing data access, the more unmanageable your security controls become.",[],{"_key":12236,"_type":99,"children":12237,"markDefs":12251,"style":799},"xxpysWtbI1TmuRkOjQIME",[12238,12242,12247],{"_key":12239,"_type":103,"marks":12240,"text":12241},"805e3bf600da",[],"Gartner’s ",{"_key":12243,"_type":103,"marks":12244,"text":12246},"02103395bb25",[12245],"Jlf7RIpbhiPHAl7T4H9gp","research",{"_key":12248,"_type":103,"marks":12249,"text":12250},"60a9e6bc8a3a",[]," reveals that by 2027, 60% of organizations will fail to realize the anticipated value of their AI use cases due to incohesive data governance frameworks. This isn’t a technology problem; it’s an architecture problem. Traditional row-level and column-level security approaches, applied asset-by-asset, simply don’t scale when you’re managing hundreds of thousands of tables across multiple business units, each with evolving compliance requirements and thousands of users requiring least-privilege access.",[12252],{"_key":12245,"_type":173,"href":12253},"https://atlan.com/gartner-data-governance/",{"_key":12255,"_type":99,"children":12256,"markDefs":12261,"style":799},"XjkTuxh_5WjdKadY_JdBU",[12257],{"_key":12258,"_type":103,"marks":12259,"text":12260},"d16c391e7e29",[],"We witnessed this firsthand while working with enterprises that were migrating from legacy data warehouses. Teams would spend weeks configuring granular permissions, only to discover that their carefully constructed access controls became obsolete the moment new data sources came online or organizational structures shifted. The governance team became the bottleneck to data democratization – precisely the opposite of what leadership wanted.",[],{"_key":12263,"_type":99,"children":12264,"markDefs":12278,"style":799},"U-COp9t-4dnh9rniNMEPI",[12265,12269,12274],{"_key":12266,"_type":103,"marks":12267,"text":12268},"349a6b7c9c10",[],"According to ",{"_key":12270,"_type":103,"marks":12271,"text":12273},"f39822181789",[12272],"RerVO2s1tA-2inegzkliT","Gartner",{"_key":12275,"_type":103,"marks":12276,"text":12277},"49b3cc9da499",[],", 77% of Chief Data and Analytics Officers put AI-ready data initiatives in their top 5 investment priorities, yet fewer than half can connect these investments to tangible business outcomes using business-driven metrics. The disconnect isn’t in data platform capabilities, it’s in how we architect access control at scale.",[12279],{"_key":12272,"_type":173,"href":12280},"https://www.gartner.com/en/articles/2025-trends-for-cdaos",{"_key":12282,"_type":99,"children":12283,"markDefs":12288,"style":799},"1bdkgT4v6bJ19DTRk5NJ-",[12284],{"_key":12285,"_type":103,"marks":12286,"text":12287},"93c8ddfd449a",[],"So how do leading enterprises solve this? They shift from managing individual permissions to orchestrating policy-driven governance that adapts automatically as data assets evolve.",[],{"_key":12290,"_type":99,"children":12291,"markDefs":12296,"style":182},"PcvlqaoZBgN4qIG5Lvx7L",[12292],{"_key":12293,"_type":103,"marks":12294,"text":12295},"8c9bb1bc664c",[],"The Cost of Governance Fragmentation",[],{"_key":12298,"_type":99,"children":12299,"markDefs":12304,"style":799},"bscun0t0tV2jSg92b6P7B",[12300],{"_key":12301,"_type":103,"marks":12302,"text":12303},"316c402e1ab4",[],"Most organizations we work with have fallen into what we call the “permission trap.” Each data asset gets its own set of access rules. Every new table requires manual configuration. Every organizational change triggers a cascade of permission updates across potentially thousands of objects.",[],{"_key":12306,"_type":99,"children":12307,"markDefs":12312,"style":799},"vtnLUVRjAOFgBZjNsOHx1",[12308],{"_key":12309,"_type":103,"marks":12310,"text":12311},"cb830d18f9d1",[],"The math is brutal. If you have 10,000 tables, each requiring separate row and column filters for different user groups, you’re managing potentially hundreds of thousands of individual permission configurations. When a new compliance regulation arrives, say, expanded PII protection requirements, you’re facing weeks of manual remediation work to identify and update every affected table.",[],{"_key":12314,"_type":99,"children":12315,"markDefs":12320,"style":799},"wcuykfwBQZbWB-9gSwhQU",[12316],{"_key":12317,"_type":103,"marks":12318,"text":12319},"287322d28876",[],"This fragmentation creates three critical failure modes. ",[],{"_key":12322,"_type":99,"children":12323,"level":230,"listItem":231,"markDefs":12328,"style":107},"aRsK3J4gVWWwVAvh5RtyV",[12324],{"_key":12325,"_type":103,"marks":12326,"text":12327},"902f1f8a03e6",[],"First, inconsistent protection across similar data assets because manual processes inevitably introduce variation. ",[],{"_key":12330,"_type":99,"children":12331,"level":230,"listItem":231,"markDefs":12336,"style":107},"chULGd7RIyzmQkZb670CH",[12332],{"_key":12333,"_type":103,"marks":12334,"text":12335},"71eb595ee37d",[],"Second, administrative overhead that scales linearly with data growth, forcing teams to choose between governance rigor and data democratization speed. ",[],{"_key":12338,"_type":99,"children":12339,"level":230,"listItem":231,"markDefs":12344,"style":107},"Fk-RERM4kxdTue1qHoYKi",[12340],{"_key":12341,"_type":103,"marks":12342,"text":12343},"bbb05ad31825",[],"Third, the inability to respond quickly to regulatory changes or security incidents because you lack centralized visibility and control.",[],{"_key":12346,"_type":99,"children":12347,"markDefs":12360,"style":799},"q1EMS40zddYPW8bHXZPDw",[12348,12352,12356],{"_key":12349,"_type":103,"marks":12350,"text":12351},"18f1e04cbfb3",[],"The cost is quantifiable: ",{"_key":12353,"_type":103,"marks":12354,"text":12273},"32822e8a53a7",[12355],"-JM4CFDBSmgpj7eyGdzXF",{"_key":12357,"_type":103,"marks":12358,"text":12359},"58abbd6d8154",[]," estimates that poor data governance costs organizations an average of $12.9 million annually in wasted resources, failed projects, and reputational damage.",[12361],{"_key":12355,"_type":173,"href":12362},"https://www.quinnox.com/blogs/data-governance-for-ai/",{"_key":12364,"_type":99,"children":12365,"markDefs":12370,"style":182},"AEFC92BZTh8vbJe1nrJsP",[12366],{"_key":12367,"_type":103,"marks":12368,"text":12369},"925308dab124",[],"Elevating Access Control to Policy Intelligence",[],{"_key":12372,"_type":99,"children":12373,"markDefs":12378,"style":799},"IF3ITZair2tBt3Cb6FkJB",[12374],{"_key":12375,"_type":103,"marks":12376,"text":12377},"cf4f418b0dbc",[],"The architectural shift that is currently being introduced is moving from object-level permissions to attribute-based policy enforcement. Think of it as graduating from tactical access control to strategic governance intelligence.",[],{"_key":12380,"_type":99,"children":12381,"markDefs":12386,"style":799},"NXi9ma_m7sBfWQA5bwz01",[12382],{"_key":12383,"_type":103,"marks":12384,"text":12385},"2f5621488d8f",[],"Attribute-Based Access Control enables governance teams to define tag-driven policies at the catalog or schema level, where they’re automatically inherited by all current and future tables and views. This approach transforms how enterprises think about data protection. Instead of securing individual tables, you’re defining principles that automatically apply across entire data domains.",[],{"_key":12388,"_type":99,"children":12389,"markDefs":12394,"style":799},"sXdXKkiIE7yiuUriQhE4k",[12390],{"_key":12391,"_type":103,"marks":12392,"text":12393},"e9fe9de9739a",[],"Here’s how this works in practice. Rather than manually configuring row filters on every customer table, you define a governance policy once: “Users can only see records where the regional attribute matches their assigned geography.” Tag your data assets with region classifications, and this policy automatically applies to every current and future table in that catalog, whether it contains customer data, transaction records, or operational metrics.",[],{"_key":12396,"_type":99,"children":12397,"markDefs":12402,"style":799},"dBok_YUWiQGGb-a2VTJTX",[12398],{"_key":12399,"_type":103,"marks":12400,"text":12401},"e9e2ea86778c",[],"The power isn’t just in simplification – it’s in adaptive, intelligent enforcement. When Data Classification automatically identifies and labels sensitive columns like email addresses or phone numbers, an ABAC policy can automatically mask those fields for all users except authorized teams. Your governance posture strengthens automatically as new data arrives, without manual intervention.",[],{"_key":12404,"_type":99,"children":12405,"markDefs":12419,"style":799},"LFDGzLN-Z4tx_5qqjEBD6",[12406,12410,12415],{"_key":12407,"_type":103,"marks":12408,"text":12409},"eb841ba18213",[],"We’ve watched this approach transform organizations. As one enterprise technology leader ",{"_key":12411,"_type":103,"marks":12412,"text":12414},"81b800c06768",[12413],"qooaBgMGSTi-xmXYLZzIM","noted",{"_key":12416,"_type":103,"marks":12417,"text":12418},"c885a76ad6ec",[],": “Databricks ABAC with column masking unblocked a major workflow for us by enabling dynamic masking of sensitive datasets at scale. The centralized hierarchical policy design brings simplicity and flexibility to policy management and enforcement”.",[12420],{"_key":12413,"_type":173,"href":12421},"https://www.databricks.com/blog/how-scale-data-governance-attribute-based-access-control-unity-catalog?utm_source=bambu&utm_medium=social&utm_campaign=advocacy&blaid=8085674",{"_key":12423,"_type":99,"children":12424,"markDefs":12429,"style":182},"k5uEyDNko6uG_7QDv9MXq",[12425],{"_key":12426,"_type":103,"marks":12427,"text":12428},"4a502c497541",[],"From Reactive Compliance to Proactive Protection",[],{"_key":12431,"_type":99,"children":12432,"markDefs":12437,"style":799},"pdBYcKeONXucP-bLGZ_Iz",[12433],{"_key":12434,"_type":103,"marks":12435,"text":12436},"ed4d0dd2527f",[],"The real strategic value emerges when you shift from reactive governance, responding to compliance requirements after they arrive, to proactive, principle-based protection that adapts automatically.",[],{"_key":12439,"_type":99,"children":12440,"markDefs":12445,"style":799},"ePVGTzFZqsqAPITDrWyYG",[12441],{"_key":12442,"_type":103,"marks":12443,"text":12444},"13c5127e829c",[],"Consider a realistic enterprise scenario: your organization acquires another company. Suddenly, you need to integrate their customer data while maintaining strict compliance boundaries during the integration period. With traditional row-level security, you’re looking at weeks of manual work mapping permissions across potentially thousands of tables.",[],{"_key":12447,"_type":99,"children":12448,"markDefs":12453,"style":799},"A5UKLhvSXgVD2TeVKfFr5",[12449],{"_key":12450,"_type":103,"marks":12451,"text":12452},"72ff172c3603",[],"With attribute-based governance, you define the integration policy once: “Users in acquiring company can access all customer records except those tagged as requiring special consent.” Tag the appropriate data assets, and the policy applies automatically. As the integration progresses and restrictions lift, you modify the policy once rather than updating thousands of individual permissions.",[],{"_key":12455,"_type":99,"children":12456,"markDefs":12461,"style":799},"z2oyBdSEPsTPYhhTqlkan",[12457],{"_key":12458,"_type":103,"marks":12459,"text":12460},"11cbe0418509",[],"This approach scales across the most complex enterprise scenarios.",[],{"_key":12463,"_type":99,"children":12464,"level":230,"listItem":231,"markDefs":12469,"style":107},"a89lqTpY5TbPjqCM8rK03",[12465],{"_key":12466,"_type":103,"marks":12467,"text":12468},"5d21d5bc3509",[],"Multi-national organizations can define region-specific data residency policies that automatically enforce as data moves across geographic boundaries. ",[],{"_key":12471,"_type":99,"children":12472,"level":230,"listItem":231,"markDefs":12477,"style":107},"tJ5qts0pr_xPa3lEceKNA",[12473],{"_key":12474,"_type":103,"marks":12475,"text":12476},"597b8930750d",[],"Financial services firms can implement dynamic masking that adapts based on user role, data sensitivity classification, and regulatory context, all without manual per-table configuration.",[],{"_key":12479,"_type":99,"children":12480,"markDefs":12485,"style":799},"CBXzhj2rMjHhdgIg9WxAT",[12481],{"_key":12482,"_type":103,"marks":12483,"text":12484},"afe02126d3c9",[],"The measurable outcomes include 60-80% reduction in governance administration time, 90%+ improvement in policy consistency across similar data assets, and the ability to respond to new compliance requirements in days rather than months.",[],{"_key":12487,"_type":99,"children":12488,"markDefs":12493,"style":182},"DzLMPwjkrm39Vhav0ZMDz",[12489],{"_key":12490,"_type":103,"marks":12491,"text":12492},"4352ce663953",[],"The Competitive Stakes",[],{"_key":12495,"_type":99,"children":12496,"markDefs":12501,"style":799},"5jgy6TO6b8mwgc9vXSj_l",[12497],{"_key":12498,"_type":103,"marks":12499,"text":12500},"1e386bb82d95",[],"We opened by describing a governance paradox, but we think the real challenge facing enterprises today is a governance threshold. Below a certain scale, perhaps a few hundred tables, a few dozen analysts, traditional permission management is adequate, if inefficient.",[],{"_key":12503,"_type":99,"children":12504,"markDefs":12509,"style":799},"NNyqEjCqS17Q3xBftQ-dW",[12505],{"_key":12506,"_type":103,"marks":12507,"text":12508},"7731d5ee1f73",[],"But once you cross that threshold, when you’re trying to democratize data access across thousands of users, tens of thousands of tables, and multiple regulatory jurisdictions, fragmented, object-level governance becomes an existential constraint on your ability to operationalize AI and analytics at competitive speed.",[],{"_key":12511,"_type":99,"children":12512,"markDefs":12525,"style":799},"szAhMpieAWDa0LUz6lHDC",[12513,12517,12521],{"_key":12514,"_type":103,"marks":12515,"text":12516},"ebdaacba70fb",[],"As Gartner’s ",{"_key":12518,"_type":103,"marks":12519,"text":12246},"3a645dca6f33",[12520],"rO5gulpuxARLJhp46r9Ii",{"_key":12522,"_type":103,"marks":12523,"text":12524},"e1c03213b7aa",[]," emphasizes, without unified governance, organizations risk data silos, compliance failures, and untrustworthy AI. A strong governance foundation accelerates time to insight, improves data trust, and allows teams to innovate confidently at scale.",[12526],{"_key":12520,"_type":173,"href":12527},"https://www.analytica.net/blogs/gartner-2025-ai-governance-and-data-strategy/",{"_key":12529,"_type":99,"children":12530,"markDefs":12535,"style":799},"LBUOmmO9K6Ui4bU37gRmf",[12531],{"_key":12532,"_type":103,"marks":12533,"text":12534},"3c1f88f9a266",[],"The enterprises winning this transition aren’t necessarily those with the most sophisticated data science teams or the largest technology budgets. They’re the ones who’ve recognized that data governance architecture is strategic infrastructure and have invested in approaches that scale governance capabilities as fast as data democratization requirements.",[],{"_key":12537,"_type":99,"children":12538,"markDefs":12543,"style":799},"vDRerT6PseKsBKO4HBOj0",[12539],{"_key":12540,"_type":103,"marks":12541,"text":12542},"866195dc9b02",[3055],"So here’s our question for you: Is your governance architecture designed to scale with your ambitions, or is it the hidden constraint limiting what your organization can achieve with data and 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Yet only 31% of enterprises report having governance capabilities robust enough to support their AI ambitions.",[],{"_key":12905,"_type":99,"children":12906,"markDefs":12911,"style":799},"66gxfx-jYZJ6jzFKtX7_7",[12907],{"_key":12908,"_type":103,"marks":12909,"text":12910},"db83169e410f",[],"The fundamental challenge isn’t whether to prioritize governance over innovation (or vice versa), but rather how to reconceptualize governance itself, transforming it from a defensive control mechanism into a strategic enabler that accelerates responsible AI development. So how do leading enterprises address this governance paradox to fuel AI-powered transformation?",[],{"_key":12913,"_type":99,"children":12914,"markDefs":12919,"style":182},"_iZsx_gNjBfm8ajMk0Mnt",[12915],{"_key":12916,"_type":103,"marks":12917,"text":12918},"e812f3bf005a",[],"The Evolution from Defensive to Enabling Governance",[],{"_key":12921,"_type":99,"children":12922,"markDefs":12927,"style":799},"pVtu7X3B36_rnKG0FF0jw",[12923],{"_key":12924,"_type":103,"marks":12925,"text":12926},"ff3ee7ad47b9",[],"Traditional data governance programs were designed with a singular focus: risk mitigation. They emerged from regulatory pressures and privacy concerns, resulting in frameworks optimized for control rather than value creation. In practice, this meant centralized data teams serving as gatekeepers, extensive approval workflows, and limited self-service capabilities.",[],{"_key":12929,"_type":99,"children":12930,"markDefs":12935,"style":799},"vWGnLe0Ea8xif9vLoeUAb",[12931],{"_key":12932,"_type":103,"marks":12933,"text":12934},"7b361ca9ae3f",[],"While this approach offered a sense of security, it created significant bottlenecks. At a global financial services firm, their legacy governance model required an average of 22 days for data scientists to access needed datasets – effectively crippling their ability to iterate on AI models at competitive speeds.",[],{"_key":12937,"_type":99,"children":12938,"markDefs":12943,"style":799},"lpboPlgJNIMk02dsf4P9D",[12939],{"_key":12940,"_type":103,"marks":12941,"text":12942},"30209ecda386",[],"Modern governance frameworks serve a fundamentally different purpose. Rather than simply restricting access, they create trusted data foundations that enable broader, safer usage. This requires unified visibility across data assets, automated policy enforcement, and fine-grained access controls that work at scale.",[],{"_key":12945,"_type":99,"children":12946,"markDefs":12951,"style":799},"5z8Kz6UU1B1LZKk1OcdFo",[12947],{"_key":12948,"_type":103,"marks":12949,"text":12950},"710df0562e97",[],"The contrast becomes clear when examining governance capabilities within Databricks’ lakehouse architecture. Rather than manually tracking permissions across fragmented systems, Unity Catalog provides a single governance layer spanning structured, semi-structured, and unstructured data, allowing organizations to implement consistent controls while dramatically expanding safe access.",[],{"_key":12953,"_type":99,"children":12954,"markDefs":12959,"style":182},"URaBDhITmVIjCzD1IjcYx",[12955],{"_key":12956,"_type":103,"marks":12957,"text":12958},"d9673320fb12",[],"Decentralizing Governance for AI Scale",[],{"_key":12961,"_type":99,"children":12962,"markDefs":12967,"style":799},"E8bp_mQoen9yUkhx0bLJy",[12963],{"_key":12964,"_type":103,"marks":12965,"text":12966},"20bad7c86620",[],"Another critical evolution involves shifting from centralized to distributed governance models. In traditional approaches, a small team of data stewards shoulders the entire governance burden, creating inevitable bottlenecks as AI initiatives scale.",[],{"_key":12969,"_type":99,"children":12970,"markDefs":12975,"style":799},"q8yS0YmFIE2GDc8lRHB8i",[12971],{"_key":12972,"_type":103,"marks":12973,"text":12974},"f359969a69e5",[],"Forward-thinking enterprises are adopting domain-oriented governance models where accountability is distributed across business units while maintaining centralized visibility. This allows organizations to scale governance efforts proportionally with their data estates.",[],{"_key":12977,"_type":99,"children":12978,"markDefs":12983,"style":799},"Z9ED24mLfBCJ39VQPSHgc",[12979],{"_key":12980,"_type":103,"marks":12981,"text":12982},"d5ba141f609f",[],"A company we worked with implemented this approach by establishing clear data domains aligned to business functions, with designated domain owners responsible for quality, metadata, and access policies within their purview. The central data governance team transitioned from gatekeeping to enablement, establishing standards, providing tooling, and monitoring compliance.",[],{"_key":12985,"_type":99,"children":12986,"markDefs":12991,"style":799},"gQR-s2Bv85UEO88D02z7I",[12987],{"_key":12988,"_type":103,"marks":12989,"text":12990},"5c56a0e43e88",[],"This distributed model proved transformative for their AI initiatives. Rather than waiting weeks for governance approvals, data scientists could access pre-approved, business-context-rich datasets through self-service catalogs. The organization accelerated AI development cycles by 70% while simultaneously strengthening its compliance posture.",[],{"_key":12993,"_type":99,"children":12994,"markDefs":12999,"style":799},"glAAq7KqUPFdCULbms8HY",[12995],{"_key":12996,"_type":103,"marks":12997,"text":12998},"5e9bc3e3c341",[],"Similar capabilities exist within modern data platforms like Databricks, where data can be organized into discrete catalogs with delegated administration while maintaining enterprise-wide visibility and policy enforcement through Unity Catalog.",[],{"_key":13001,"_type":99,"children":13002,"markDefs":13007,"style":182},"E5HIA3iR1NYCfd2z_TtY8",[13003],{"_key":13004,"_type":103,"marks":13005,"text":13006},"976a902fdedf",[],"From Static Rules to Dynamic, Context-Aware Governance",[],{"_key":13009,"_type":99,"children":13010,"markDefs":13015,"style":799},"pxhZ13ZYNnbo7DHFU-Ovu",[13011],{"_key":13012,"_type":103,"marks":13013,"text":13014},"e651369f31a7",[],"Perhaps the most significant shift is from static, rule-based governance to dynamic, context-aware approaches. Traditional governance applied one-size-fits-all policies regardless of the user, workload, or sensitivity level, essentially treating all data and use cases equally.",[],{"_key":13017,"_type":99,"children":13018,"markDefs":13023,"style":799},"mphGZ9oH39AwgwlelTNrp",[13019],{"_key":13020,"_type":103,"marks":13021,"text":13022},"951962626b46",[],"Leading organizations now implement dynamic governance that adapts based on context. This includes:",[],{"_key":13025,"_type":99,"children":13026,"markDefs":13031,"style":799},"tFgczjLEkgwa1-34WcnOQ",[13027],{"_key":13028,"_type":103,"marks":13029,"text":13030},"745b8c622859",[],"– Differential privacy controls that automatically adjust based on dataset sensitivity\n– Purpose-based access that considers not just who you are, but what you’re doing\n– Automated lineage tracking that provides end-to-end visibility of data flows",[],{"_key":13033,"_type":99,"children":13034,"markDefs":13039,"style":799},"dsI0RW7IrMpNfB5LLsrY4",[13035],{"_key":13036,"_type":103,"marks":13037,"text":13038},"d3c1b6ad71d6",[],"A global retailer implemented this approach using Databricks’ fine-grained access controls and lineage capabilities. Their data scientists received broader access to customer data for model development, but with automatic PII masking and usage limitations enforced by the platform rather than manual processes. When models moved to production, the governance controls followed the data through its lifecycle, ensuring consistent protection without manual handoffs.",[],{"_key":13041,"_type":99,"children":13042,"markDefs":13047,"style":799},"e9EFulV_LqXOqCQqgUJPM",[13043],{"_key":13044,"_type":103,"marks":13045,"text":13046},"24dd5f14d544",[],"The result? Their data science teams increased productivity by 40% while reducing governance-related incidents by 60% – a dual outcome impossible under traditional approaches.",[],{"_key":13049,"_type":99,"children":13050,"markDefs":13055,"style":182},"d6asnM0bh3R0DpmjEJvMW",[13051],{"_key":13052,"_type":103,"marks":13053,"text":13054},"f4da1c625de9",[],"Conclusion: Governance as AI Accelerator",[],{"_key":13057,"_type":99,"children":13058,"markDefs":13063,"style":799},"-4SQyOankfAgRL6754yyw",[13059],{"_key":13060,"_type":103,"marks":13061,"text":13062},"43819450d948",[],"The evidence is clear: organizations that reimagine governance as a strategic enabler rather than a necessary burden gain significant competitive advantages in their AI initiatives. By shifting from defensive to enabling models, centralizing policy while decentralizing execution, and implementing context-aware controls, enterprises can simultaneously strengthen protection and accelerate innovation.",[],{"_key":13065,"_type":99,"children":13066,"markDefs":13071,"style":799},"QwjoEeGvjFUZlgbsIGdsF",[13067],{"_key":13068,"_type":103,"marks":13069,"text":13070},"957f41ce0bf1",[],"The path forward requires more than technology – it demands a fundamental shift in how organizations conceptualize governance itself. Rather than asking “how do we control our data?” the more valuable question becomes “how do we enable safe, efficient use of our data at scale?”",[],{"_key":13073,"_type":99,"children":13074,"markDefs":13079,"style":799},"TM3laPDaAyIyyrHDiAa32",[13075],{"_key":13076,"_type":103,"marks":13077,"text":13078},"fb780e996ecf",[],"As AI becomes increasingly central to competitive strategy, this governance transformation grows more urgent. Those clinging to outdated governance paradigms will find themselves unable to unlock the value of their data while watching more agile competitors race ahead.",[],{"_key":13081,"_type":99,"children":13082,"markDefs":13087,"style":799},"cIMb6ILDDRbANVv1Taklf",[13083],{"_key":13084,"_type":103,"marks":13085,"text":13086},"a053f29a9285",[],"We encourage you to reflect: Is your governance framework designed primarily to prevent problems, or does it actively enable your AI ambitions? 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you’re leading enterprise technology today, you’ve probably had this thought more than once: “We’re spending too much on data infrastructure and still moving too slowly.”",[],{"_key":13189,"_type":99,"children":13190,"markDefs":13195,"style":799},"8NydqIkUpnHIiUaNBXeDp",[13191],{"_key":13192,"_type":103,"marks":13193,"text":13194},"01c40cec55fb",[],"Data warehouses, data lakes, integration tools, pipelines, governance layers, visualization platforms… it all adds up. 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This allows executives to have a complete view of the overall performance of their business and the different departments. Nevertheless, there are certain technical and business terms in BI reporting that team members in organizations need to know. That is so because mastery of the key terms in BI reporting can significantly enhance the ability to leverage it effectively.",[],{"_key":19177,"_type":99,"children":19178,"markDefs":19183,"style":182},"IUpNIm0VSlekSkamf2iFM",[19179],{"_key":19180,"_type":103,"marks":19181,"text":19182},"daacc3ff725c",[],"The foundation of BI Reporting Terminology",[],{"_key":19185,"_type":99,"children":19186,"markDefs":19191,"style":799},"b2uHZ1XvZQo1ZcZxnQn0R",[19187],{"_key":19188,"_type":103,"marks":19189,"text":19190},"b794ee682f55",[],"There are three core building blocks in Business Intelligence: Data Ingestion, Data Warehousing and BI. Data Ingestion is the process of combining data from different sources and bringing it together to provide a unified view ultimately. Data Warehousing is the process of storing and staging information and optimizing it for access and analysis in a company. Finally, BI is the visible portion of the business data systems that enables access and delivery of information to business users. We will look at the key terms for each of the three parts.",[],{"_key":19193,"_type":99,"children":19194,"markDefs":19199,"style":182},"PGFq1cTkW5GsUz8uNFapr",[19195],{"_key":19196,"_type":103,"marks":19197,"text":19198},"798a81229d51",[],"Data Ingestion Key Terms",[],{"_key":19201,"_type":99,"children":19202,"markDefs":19211,"style":799},"HOAUNCW5MTV-fhtBBhHZo",[19203,19207],{"_key":19204,"_type":103,"marks":19205,"text":19206},"9531d0f31cf3",[3055],"Structured data",{"_key":19208,"_type":103,"marks":19209,"text":19210},"78966b971d3c",[],"— Structured data refers to data that adheres to a specific format or schema, making it easily searchable and organized in databases. It is typically stored in relational databases and is characterized by its high level of organization, such as in rows and columns, which makes it easy to enter, query, and analyze.",[],{"_key":19213,"_type":99,"children":19214,"markDefs":19223,"style":799},"18cU8PwigOH-7BJIxXkwR",[19215,19219],{"_key":19216,"_type":103,"marks":19217,"text":19218},"834417b16e61",[3055],"Data governance",{"_key":19220,"_type":103,"marks":19221,"text":19222},"eaf9357f2e94",[],"—A process that enforces consistent definitions, rules, business metrics, policies, and procedures for how a company treats its data. It can encompass many areas including data creation, movement, transformation, integration, and definitions, all the way to consumption. A data governance program helps the organization treat its data as a corporate asset and maximize its value.",[],{"_key":19225,"_type":99,"children":19226,"markDefs":19235,"style":799},"dVZb6Oyoaxi9jrj2xgxMT",[19227,19231],{"_key":19228,"_type":103,"marks":19229,"text":19230},"90e7a517370b",[3055],"Data cleansing",{"_key":19232,"_type":103,"marks":19233,"text":19234},"d3716855a8c2",[],"—Finding and fixing errors, inconsistencies and inaccuracies in data. The level of cleanliness required depends on each industry’s best practices. Tools for Data quality are used for the more complex processing while data integration tools perform basic processing.",[],{"_key":19237,"_type":99,"children":19238,"markDefs":19243,"style":182},"ste1Lip2dpR3OqyXAHKUC",[19239],{"_key":19240,"_type":103,"marks":19241,"text":19242},"88a55a2e8f97",[],"Data Warehousing Key Terms",[],{"_key":19245,"_type":99,"children":19246,"markDefs":19255,"style":799},"H9oztfzGEei3PGnYmjy_M",[19247,19251],{"_key":19248,"_type":103,"marks":19249,"text":19250},"9fc74c66e012",[3055],"Data quality",{"_key":19252,"_type":103,"marks":19253,"text":19254},"6c7441d63890",[],"—Achieved when data embodies the “five Cs”: clean, consistent, conformed, current, and comprehensive.",[],{"_key":19257,"_type":99,"children":19258,"markDefs":19267,"style":799},"Fc1jLay515BrjqwY4VGC-",[19259,19263],{"_key":19260,"_type":103,"marks":19261,"text":19262},"d7a29fcefa25",[3055],"ETL (extract, transform, and load)",{"_key":19264,"_type":103,"marks":19265,"text":19266},"6e1587c5cc55",[],"—The process in which data is taken from the source system, configured, and stored in a data warehouse or database. ETL tools automate data integration tasks.",[],{"_key":19269,"_type":99,"children":19270,"markDefs":19279,"style":799},"YqD02Xg7SkpVXUDWStrTI",[19271,19275],{"_key":19272,"_type":103,"marks":19273,"text":19274},"6bb108fbd0bf",[3055],"Data preparation",{"_key":19276,"_type":103,"marks":19277,"text":19278},"c6bebcbfe13d",[],"—The core set of processes for data integration. These processes gather data from diverse source systems and transform it according to business and technical rules. Afterward, another process stages it for later steps in its life cycle when it becomes information used by information consumers.",[],{"_key":19281,"_type":99,"children":19282,"markDefs":19287,"style":182},"30l2MWy2Wu8_RJfE4wumT",[19283],{"_key":19284,"_type":103,"marks":19285,"text":19286},"68c3d816e8bb",[],"Business Intelligence Key Terms",[],{"_key":19289,"_type":99,"children":19290,"markDefs":19298,"style":799},"rRnYGB63GePenQWXtyW4I",[19291,19294],{"_key":19292,"_type":103,"marks":19293,"text":12147},"9163f8c76222",[3055],{"_key":19295,"_type":103,"marks":19296,"text":19297},"db0dace5d2d5",[],"—The examination of information to uncover insights that give a business person",[],{"_key":19300,"_type":99,"children":19301,"markDefs":19306,"style":799},"VBpEL6W1Tqzknckz_1shT",[19302],{"_key":19303,"_type":103,"marks":19304,"text":19305},"328b4c3dcb3d",[],"the knowledge to make informed decisions. Analytics tools enable people to query and analyze information using data visualization to communicate findings in an easy-to-understand way. There are different analytical types: descriptive (what happened), diagnostic (why it",[],{"_key":19308,"_type":99,"children":19309,"markDefs":19314,"style":799},"9XPzDAfbwAdmEANQj4LpU",[19310],{"_key":19311,"_type":103,"marks":19312,"text":19313},"0942955af96d",[],"happened), predictive (what is likely to happen) and prescriptive (what actions should be taken).",[],{"_key":19316,"_type":99,"children":19317,"markDefs":19326,"style":799},"HkAGRTA-mtM1LBSjY_HkR",[19318,19322],{"_key":19319,"_type":103,"marks":19320,"text":19321},"e9567467cad9",[3055],"Reporting",{"_key":19323,"_type":103,"marks":19324,"text":19325},"243393c4b240",[],"—Collecting data from various sources and presenting it to business people in an understandable way so they can analyze it. This is the core BI style. Reports were initially static with predefined formats but have become interactive and customizable.",[],{"_key":19328,"_type":99,"children":19329,"markDefs":19338,"style":799},"QGxhK-6ciVmGWA_X3vTPd",[19330,19334],{"_key":19331,"_type":103,"marks":19332,"text":19333},"6a4a30b9ffd7",[3055],"Data visualization",{"_key":19335,"_type":103,"marks":19336,"text":19337},"553f18717c44",[],"—Visually presenting data, such as graphs and charts, helps business people see insights they might not otherwise discern from tabular data. Data visualization is only as effective as the quality of the data it draws upon.",[],{"_key":19340,"_type":99,"children":19341,"markDefs":19350,"style":799},"Y_oN2igpKO6Lsr4iRDmru",[19342,19346],{"_key":19343,"_type":103,"marks":19344,"text":19345},"094988d9fde4",[3055],"Dashboards",{"_key":19347,"_type":103,"marks":19348,"text":19349},"d24285f56fd2",[],"—This BI tool displays numeric and graphical information on a single display, making it easy for a business person to get information from different sources and customize the appearance. ",[],{"_key":19352,"_type":99,"children":19353,"markDefs":19358,"style":799},"rNTY05GzaXTaXXCFeHTJL",[19354],{"_key":19355,"_type":103,"marks":19356,"text":19357},"d48eedec4f88",[],"Understanding the key terms in BI reporting is crucial as they form the language through which data insights are communicated. This understanding is not just beneficial for data analysts but also essential for business decision-makers. Knowing proper BI terminology enables effective team communication, facilitates a better understanding of reports and dashboards, and empowers decision-makers to ask the right questions, leading to informed strategic decisions.",[],{"_key":19360,"_type":99,"children":19361,"markDefs":19375,"style":799},"WOFL8sEtScS7bP6wcm3Ri",[19362,19366,19371],{"_key":19363,"_type":103,"marks":19364,"text":19365},"d4204fb3cc57",[],"Contact us and let’s help you in your BI journey! However, if you want to learn more about our capabilities, check out our ",{"_key":19367,"_type":103,"marks":19368,"text":19370},"63c47b588f04",[19369],"yxVNlBVSwh242Oru96Pht","services",{"_key":19372,"_type":103,"marks":19373,"text":19374},"ecd99440ccf3",[]," page. ",[19376],{"_key":19369,"_type":173,"href":19377},"https://cosmosthrace.com/our-data-and-ai-services/",{"_type":17,"current":19156},[19380,19387],{"_createdAt":19381,"_id":19382,"_rev":19383,"_type":8636,"_updatedAt":19384,"name":19385,"orderRank":10508,"uid":19386},"2026-01-20T12:24:14Z","b076b6a6-d33d-43cc-b2b8-bde54029e56e","n91tOxoMUaPULCyHfFvzCV","2026-01-20T12:24:17Z","Power BI","power-bi",{"_createdAt":12143,"_id":12144,"_rev":12145,"_type":8636,"_updatedAt":12146,"name":12147,"orderRank":12148,"uid":12149},{"_createdAt":19389,"_id":19390,"_rev":19391,"_system":19392,"_type":72,"_updatedAt":19395,"archived":126,"author":161,"category":19396,"date":19400,"description":19401,"image":161,"name":19410,"oldSlug":19411,"orderRank":11548,"reviewer":161,"sections":19412,"seo":161,"slug":19538,"tags":19539},"2026-01-15T15:49:42Z","0fcb7e51-550c-45cf-aea5-a2ddad6560b2","7hw4Cb1llohacCi9MHuWPr",{"base":19393},{"id":19390,"rev":19394},"YkA36qTDOerM1fSJamXmN1","2026-01-28T08:35:46Z",{"_createdAt":32,"_id":33,"_rev":34,"_system":19397,"_type":12,"_updatedAt":38,"name":39,"orderRank":40,"slug":19399,"uid":42},{"base":19398},{"id":33,"rev":37},{"_type":17,"current":42},"2024-01-31",[19402],{"_key":19403,"_type":99,"children":19404,"markDefs":19409,"style":107},"d495d98a1111",[19405],{"_key":19406,"_type":103,"marks":19407,"text":19408},"fc0e03f6ba8d",[],"Having a holistic view of your business is crucial if you want to outperform your competitors. However, achieving that overview of your company can become",[],"What are the top 5 best practices in Business Intelligence reporting?","top-5-best-practices-in-business-intelligence-reporting",[19413],{"_createdAt":19414,"_id":19415,"_key":19416,"_ref":19415,"_rev":19394,"_type":168,"_updatedAt":19414,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":19417,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:27Z","UFJL5x9x57tevfocwoQ8l","LoRUDO5PqWU-lMm1gaD72",[19418,19425,19432,19439,19446,19453,19460,19467,19474,19481,19488,19495,19502,19509,19516],{"_key":19419,"_type":99,"children":19420,"markDefs":19424,"style":799},"4K_gD5F35psnbfQQk2Twg",[19421],{"_type":103,"marks":19422,"text":19423},[],"Having a holistic view of your business is crucial if you want to outperform your competitors. However, achieving that overview of your company can become a burdensome task, if not done properly. Nowadays, everyone hops on the BI trend to achieve that. Nevertheless, BI should be done properly in order to achieve tangible results. In this article, we will present you the 5 best practices in Business Intelligence reporting that can help your business thrive.",[],{"_key":19426,"_type":99,"children":19427,"markDefs":19431,"style":170},"4ZrPztYIA-zOAnm8Drbr9",[19428],{"_type":103,"marks":19429,"text":19430},[],"Start with Questions and Understand Your Audience:",[],{"_key":19433,"_type":99,"children":19434,"markDefs":19438,"style":799},"lL38Z4BqU4rI7T-lZwuZY",[19435],{"_type":103,"marks":19436,"text":19437},[],"Before delving into BI reporting, it’s crucial to identify the specific insights you need and understand who the reporting audience is. This involves asking the right questions to pinpoint what you seek to understand and knowing who will use your BI reports. This step helps tailor the data and insights to the needs of different groups within your organization, such as executives requiring summarized information versus operational managers who may need more detailed data​​​​.",[],{"_key":19440,"_type":99,"children":19441,"markDefs":19445,"style":170},"CudeNfJnPc6QRdbz1ZpgG",[19442],{"_type":103,"marks":19443,"text":19444},[],"Ensure Data Quality and Identify Required Data Sources:",[],{"_key":19447,"_type":99,"children":19448,"markDefs":19452,"style":799},"I9OOakCoVHYeGsWKvf1zE",[19449],{"_type":103,"marks":19450,"text":19451},[],"The foundation of effective BI reporting is high-quality data. This involves ensuring the accuracy, reliability, and relevance of the data used. Poor data quality can lead to misguided decisions. Additionally, identifying and securing access to the necessary data sources is essential for a comprehensive BI reporting system​​​​.",[],{"_key":19454,"_type":99,"children":19455,"markDefs":19459,"style":170},"cz3bvh8KQocZUTIpnMNd5",[19456],{"_type":103,"marks":19457,"text":19458},[],"Align Reports with Business Objectives and Create Mockups:",[],{"_key":19461,"_type":99,"children":19462,"markDefs":19466,"style":799},"xDJz41MYmmQvYgPHo8WjI",[19463],{"_type":103,"marks":19464,"text":19465},[],"Your BI reports should align with the overarching business objectives. This means they should be designed to address specific business goals and KPIs. Creating report mockups is also a best practice. Mockups provide a visual representation of the final reports, allowing for early feedback and adjustments before full-scale implementation​​​​.",[],{"_key":19468,"_type":99,"children":19469,"markDefs":19473,"style":170},"zIErIfbpoUXhuFRK7eP5q",[19470],{"_type":103,"marks":19471,"text":19472},[],"Visualization and User-Friendly Design:",[],{"_key":19475,"_type":99,"children":19476,"markDefs":19480,"style":799},"5dR3TxVL621z6XNcL98R6",[19477],{"_type":103,"marks":19478,"text":19479},[],"Presenting data in an easily digestible format is crucial. Effective data visualization, through the use of charts, graphs, and dashboards, enhances the understanding and usefulness of BI reports. Additionally, reports should be user-friendly, ensuring accessibility for all stakeholders regardless of their technical expertise​​​​.",[],{"_key":19482,"_type":99,"children":19483,"markDefs":19487,"style":170},"IIL_qSXGOG9B6nunc_u7M",[19484],{"_type":103,"marks":19485,"text":19486},[],"Automate Distribution and Foster a Data-driven Culture:",[],{"_key":19489,"_type":99,"children":19490,"markDefs":19494,"style":799},"eqef9PgB9klYor_BM-eAs",[19491],{"_type":103,"marks":19492,"text":19493},[]," Automating the distribution of BI reports ensures that the right stakeholders receive the right information at the right time. This approach saves time and increases efficiency. Fostering a data-driven culture within your organization encourages the use of BI reporting and promotes the utilization of actionable insights across all levels​​​​.",[],{"_key":19496,"_type":99,"children":19497,"markDefs":19501,"style":170},"WDpA97LlrMqz15jY7hfVx",[19498],{"_type":103,"marks":19499,"text":19500},[],"Business Intelligence Reporting Benefits",[],{"_key":19503,"_type":99,"children":19504,"markDefs":19508,"style":799},"d3-GcXNe-Qg6sdL6xm_uT",[19505],{"_type":103,"marks":19506,"text":19507},[],"In terms of the general benefits of BI, it allows organizations to make more informed decisions by providing comprehensive insights into various aspects of the business. This includes sales, financial performance, customer behavior, and market trends. BI tools facilitate the collection, analysis, and presentation of business data, helping leaders and managers to identify opportunities, optimize processes, and mitigate risks.",[],{"_key":19510,"_type":99,"children":19511,"markDefs":19515,"style":799},"U_In4FnRQ13frJJuF--9X",[19512],{"_type":103,"marks":19513,"text":19514},[],"Proper BI reporting is particularly beneficial for executive-level managers. It empowers them to make better-informed decisions by providing a clear, comprehensive view of operational performance and strategic opportunities. Those reports can highlight trends, reveal insights into customer behavior, track performance against goals, and much more. ",[],{"_key":19517,"_type":99,"children":19518,"markDefs":19534,"style":799},"N84vUB_DHtPztIju_f0M3",[19519,19522,19526,19529,19532],{"_type":103,"marks":19520,"text":19521},[],"In conclusion, integrating these top 5 best practices into your BI reporting process can significantly enhance the effectiveness of your business intelligence initiatives. They ensure that the BI reports are accurate, relevant, and actionable, thus empowering executive-level managers and other decision-makers to steer the organization more effectively toward its goals. ",{"_type":103,"marks":19523,"text":19525},[19524],"puaoI4aAxn_GLo0jZxS01","Contact",{"_type":103,"marks":19527,"text":19528},[]," us and let us help you implement BI reporting in your organization effectively! 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That is especially true for businesses in the IT sector that build solutions based on the data their customers generate. That is why, at Cosmos Thrace, one of our top priorities is ensuring that our client’s data is secured and protected. Achieving ISO 27001 Certification is a milestone that tells us that our security efforts are put in the right direction.",[],{"_key":19626,"_type":99,"children":19627,"markDefs":19632,"style":182},"Fk62qjsRBsZk3eWTsfoIq",[19628],{"_key":19629,"_type":103,"marks":19630,"text":19631},"e9ce561756b8",[],"What is ISO 27001 Certification?",[],{"_key":19634,"_type":99,"children":19635,"markDefs":19640,"style":799},"ntvwg_8_fu7CppGwg1TpR",[19636],{"_key":19637,"_type":103,"marks":19638,"text":19639},"510ea8259030",[],"ISO 27001 is an international standard that provides a framework for Information Security Management Systems (ISMS) to help organizations secure their information assets. This standard is part of the ISO/IEC 27000 family of standards. The standards have been developed by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC).",[],{"_key":19642,"_type":99,"children":19643,"markDefs":19648,"style":799},"tlbISW_wR8b1pO0zTvxyQ",[19644],{"_key":19645,"_type":103,"marks":19646,"text":19647},"ff494ecafe9b",[],"To achieve ISO 27001 certification, an organization must implement an ISMS following the standard’s requirements and undergo a formal audit by an accredited certification body. In our case, it is an ISMS applied to technology-based services in electronic data processing and information technology. The certification has worldwide recognition and maintaining it requires ongoing compliance and regular audits.",[],{"_key":19650,"_type":99,"children":19651,"markDefs":19656,"style":182},"z8FYRaWNLK_Zov1Q7HB71",[19652],{"_key":19653,"_type":103,"marks":19654,"text":19655},"28546e1ef9a5",[],"What does ISO 270001 mean for our clients?",[],{"_key":19658,"_type":99,"children":19659,"markDefs":19664,"style":799},"E9TuEs8wHJQb7n7RDeHJi",[19660],{"_key":19661,"_type":103,"marks":19662,"text":19663},"fea6c851c7b7",[],"The certification impacts you, as our customer, in the following ways:",[],{"_key":19666,"_type":99,"children":19667,"level":230,"listItem":4889,"markDefs":19676,"style":107},"TP2YgwJ43pZKNa8kNVD6v",[19668,19672],{"_key":19669,"_type":103,"marks":19670,"text":19671},"509b510c5d43",[3055],"Enhanced Data Security",{"_key":19673,"_type":103,"marks":19674,"text":19675},"f16fdcbd389d",[],": You can be assured that your sensitive data, such as customer information, business analytics, and proprietary AI models, are protected according to international standards. The certification means that we have established a comprehensive Information Security Management System (ISMS) that covers every aspect of data handling, from its creation to its eventual disposal.",[],{"_key":19678,"_type":99,"children":19679,"level":230,"listItem":4889,"markDefs":19688,"style":107},"DT1jw8ZLG9uB3m_HN8L8J",[19680,19684],{"_key":19681,"_type":103,"marks":19682,"text":19683},"480189224db0",[3055],"Compliance",{"_key":19685,"_type":103,"marks":19686,"text":19687},"534e99484cfa",[],": By adhering to ISO 27001 standards, Cosmos Thrace demonstrates compliance with global best practices in information security including GDPR, HIPAA, and more. This means that our data practices are recognized by many different regulators and comply with their legal requirements.",[],{"_key":19690,"_type":99,"children":19691,"level":230,"listItem":4889,"markDefs":19700,"style":107},"JpTU_aCBl0yAUhbklMsyn",[19692,19696],{"_key":19693,"_type":103,"marks":19694,"text":19695},"830e2e692992",[3055],"Risk Management and Mitigation",{"_key":19697,"_type":103,"marks":19698,"text":19699},"cfe12be7109c",[],": ISO 27001’s attention to risk assessment and mitigation is among the most emphasized activities during the certification process. Establishing proper risk mitigation strategies reassures clients that potential security risks are proactively identified and managed.",[],{"_key":19702,"_type":99,"children":19703,"level":230,"listItem":4889,"markDefs":19712,"style":107},"-djN8bBadWe93nukKom1J",[19704,19708],{"_key":19705,"_type":103,"marks":19706,"text":19707},"44ea79146b55",[3055],"Regular Monitoring and Improvement",{"_key":19709,"_type":103,"marks":19710,"text":19711},"3dc48c29c08e",[],": The ISO 27001 certification requires ongoing audits and improvements. This means that we will be monitoring and updating our security practices every month to be up to date with the latest best practices in data security. Moreover, we will be monitored by the International Security Organization so they will be providing an expert external opinion on how our security efforts are being developed. ",[],{"_key":19714,"_type":99,"children":19715,"markDefs":19720,"style":799},"lu2awz1BWy-6lEZHUECt7",[19716],{"_key":19717,"_type":103,"marks":19718,"text":19719},"074664a3413d",[],"In a nutshell, the ISO 27001 certification is not just a one-time achievement that makes our company look more reliable. This is a commitment to continuous enhancement in security practices that offer long-term reliability and safety to our clients. It is a dedication and investment into a data security strategy that in the next years is going to be the backbone of all our Business Intelligence and AI projects.",[],{"_key":19722,"_type":99,"children":19723,"markDefs":19735,"style":799},"cuSjEm0E_6WUZsbvibyNv",[19724,19728,19732],{"_key":19725,"_type":103,"marks":19726,"text":19727},"eca8cc81e48e",[],"Cosmos Thrace is a Databricks consulting partner specializing in Lakehouse architecture, Unity Catalog, and AI/ML implementations across Europe. 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This article provides a structured guide to becoming a successful BI Reporting Analyst and pursuing a career that will be both beneficial and rewarding.",[],{"_key":20019,"_type":99,"children":20020,"markDefs":20025,"style":182},"nf34523R3TXfrvR8vB0pb",[20021],{"_key":20022,"_type":103,"marks":20023,"text":20024},"172878b91db5",[],"Essential Educational Background and Technical Skills",[],{"_key":20027,"_type":99,"children":20028,"markDefs":20033,"style":799},"MGbCmCKKocH-dVyU13Gie",[20029],{"_key":20030,"_type":103,"marks":20031,"text":20032},"abf2d011a57b",[],"A solid educational foundation is crucial to embark on your journey as a BI Reporting Analyst. Degrees in computer science, statistics, or business administration are highly beneficial. 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This role requires not just analyzing data, but also effectively communicating these insights to non-technical stakeholders. Attention to detail and problem-solving abilities are paramount to ensure the accuracy and relevance of your reports.",[],{"_key":20101,"_type":99,"children":20102,"markDefs":20107,"style":799},"dIw8lhW3Q4ffsyi6euHAA",[20103],{"_key":20104,"_type":103,"marks":20105,"text":20106},"3a823ec3035c",[],"A critical aspect of this role is continuous learning. The BI field is dynamic, with new tools and techniques constantly emerging. 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While these terms are often used interchangeably, a nuanced understanding of their differences can significantly impact how organizations harness data for strategic decision-making.",[],{"_key":20242,"_type":99,"children":20243,"markDefs":20248,"style":182},"wArelsQRdnHi7qYGQVkJ4",[20244],{"_key":20245,"_type":103,"marks":20246,"text":20247},"34070e2b3311",[],"1. Scope and Purpose:",[],{"_key":20250,"_type":99,"children":20251,"markDefs":20256,"style":799},"xhbA6AAqZ5lmphhNvcRNe",[20252],{"_key":20253,"_type":103,"marks":20254,"text":20255},"cc8163ed1e48",[],"At its core, reporting is a subset of Business Intelligence. Reporting primarily involves the presentation of data in a structured format, often through charts, graphs, and tables. It provides a snapshot of historical performance and answers specific questions. On the other hand, BI encompasses a broader spectrum, including reporting but extending beyond to data analysis, predictive modeling, and strategic planning. BI is a comprehensive approach that empowers executives to not only understand what happened but also why it happened and what might happen in the future.",[],{"_key":20258,"_type":99,"children":20259,"markDefs":20264,"style":182},"9U8q6a8G4-ycYPvpF3bfS",[20260],{"_key":20261,"_type":103,"marks":20262,"text":20263},"c78c255e3e63",[],"2. Time Horizon:",[],{"_key":20266,"_type":99,"children":20267,"markDefs":20272,"style":799},"d5-5aRaX0uCtGAy7sxwhy",[20268],{"_key":20269,"_type":103,"marks":20270,"text":20271},"e2b1bbfd5edc",[],"One key difference between BI and reporting lies in their time horizons. Reporting typically deals with historical data, offering a retrospective view of past performance. In contrast, BI incorporates historical data but also focuses on the present and future. It equips executives with real-time insights, enabling proactive decision-making based on current market conditions and emerging trends.",[],{"_key":20274,"_type":99,"children":20275,"markDefs":20280,"style":182},"CeUGzQwFiw_j1hsllCCyX",[20276],{"_key":20277,"_type":103,"marks":20278,"text":20279},"9984775bbd8d",[],"3. Interactivity and Flexibility:",[],{"_key":20282,"_type":99,"children":20283,"markDefs":20288,"style":799},"d4bfHl_0aZn1YzM-lfpNh",[20284],{"_key":20285,"_type":103,"marks":20286,"text":20287},"276a8a4e0cc2",[],"Reporting often follows a predefined format, providing a static view of data. BI, however, emphasizes interactivity and flexibility. Business Intelligence tools enable executives to explore data dynamically, drill down into details, and generate ad-hoc reports tailored to specific queries. This flexibility is vital in a rapidly changing business environment where executives need to adapt swiftly to new information.",[],{"_key":20290,"_type":99,"children":20291,"markDefs":20296,"style":182},"NlIfc-Pfy3a-59d8z24dG",[20292],{"_key":20293,"_type":103,"marks":20294,"text":20295},"cbf7b84e873d",[],"4. Data Complexity and Sources:",[],{"_key":20298,"_type":99,"children":20299,"markDefs":20304,"style":799},"qWnP9cE8dMbY6hBPsXxXP",[20300],{"_key":20301,"_type":103,"marks":20302,"text":20303},"f6927a76a1e6",[],"While reporting tends to deal with structured data in a standardized format, Business Intelligence tackles a broader range of data complexities. BI solutions can handle diverse data sources, including unstructured data, providing a more comprehensive view of the business landscape. This capability allows executives to glean insights from various channels, from traditional databases to social media and beyond.",[],{"_key":20306,"_type":99,"children":20307,"markDefs":20312,"style":182},"iwZwIRqNYUZEQ-6uDmU2Z",[20308],{"_key":20309,"_type":103,"marks":20310,"text":20311},"bdd840f26a86",[],"5. Decision Support:",[],{"_key":20314,"_type":99,"children":20315,"markDefs":20320,"style":799},"Y7k1LkCDaugPFa96giyV1",[20316],{"_key":20317,"_type":103,"marks":20318,"text":20319},"4368151544f2",[],"Reporting primarily serves as a tool for tracking Key Performance Indicators (KPIs) and operational metrics. Business Intelligence, on the other hand, goes a step further by offering decision support. BI tools incorporate advanced analytics and predictive modeling, empowering executives to make strategic decisions based on a deeper understanding of trends and patterns.",[],{"_key":20322,"_type":99,"children":20323,"markDefs":20328,"style":182},"IaVlh6QEkBPIB2LE_V9Nt",[20324],{"_key":20325,"_type":103,"marks":20326,"text":20327},"38097e9b7019",[],"6. Integration with Strategic Planning:",[],{"_key":20330,"_type":99,"children":20331,"markDefs":20336,"style":799},"lc-1hcvIj6X1tRVPCXgWo",[20332],{"_key":20333,"_type":103,"marks":20334,"text":20335},"b1a4a1d207f0",[],"While reporting informs tactical decisions, BI is inherently tied to strategic planning. Business Intelligence aligns data insights with organizational goals, facilitating long-term planning and helping executives make decisions that contribute to the overall business strategy.",[],{"_key":20338,"_type":99,"children":20339,"markDefs":20344,"style":799},"p7FO_TqdcFNiclCCiHMvK",[20340],{"_key":20341,"_type":103,"marks":20342,"text":20343},"3c58ca111c94",[],"In conclusion, understanding the difference between Business Intelligence and reporting is pivotal for business executives aiming to leverage data effectively. The nuanced capabilities of BI extend beyond traditional reporting, providing a holistic approach to data analysis, decision support, and strategic planning. By embracing both reporting and BI, executives can create a well-rounded approach to data-driven decision-making, ensuring agility and competitiveness in today’s dynamic business 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are delighted to announce that we have secured our first Horizon flexible laser-based manufacturing through a precision photon distribution (FLASH) project, in recognition 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the start of our Horizon journey","start-of-our-horizon-journey",[20408],{"_createdAt":20409,"_id":20410,"_key":20411,"_ref":20410,"_rev":20412,"_system":20413,"_type":168,"_updatedAt":20415,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":20416,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:43:49Z","vDdSUfUtSXSqi3GhcNGmC","a47KSyjvDO05AVFtzo-vE","3FmTMVHFg5qVDXbdIwDsKr",{"base":20414},{"id":20410,"rev":20355},"2026-01-26T13:20:31Z",[20417,20436,20444,20452,20460,20468,20476,20484,20492,20500,20508,20516,20524,20532,20543,20554,20565,20576,20587,20598,20609,20620,20631,20646,20657,20668,20679,20690],{"_key":20418,"_type":99,"children":20419,"markDefs":20433,"style":799},"pYczSyDHKQ9vdh6g82tte",[20420,20424,20429],{"_key":20421,"_type":103,"marks":20422,"text":20423},"7c6b0ff416c8",[],"We are delighted to announce that we have secured our first ",{"_key":20425,"_type":103,"marks":20426,"text":20428},"5e71bebd4ad9",[20427],"Y93ciLhhDz9pBOwQwLLMG","Horizon",{"_key":20430,"_type":103,"marks":20431,"text":20432},"2409f8c7f104",[]," project, called flexible laser-based manufacturing through a precision photon distribution (FLASH), in recognition of our expertise in innovation, technology and manufacturing. We are grateful and excited to be one of the few SME companies from our EU region to win a place on a project of this size and start their Horizon journey. Our role in the € 4 131 800.25 three-year project will be to develop machine learning algorithms to better predict and recommend the optimal processing regimes across the platform. Winning a place in a consortium alongside other highly experienced companies is evidence of the expertise of our team and the trust that other organizations have in us. The news marks an exciting end to 2023 and points to a great start to 2024, with the project launching in January.",[20434],{"_key":20427,"_type":173,"href":20435},"https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe_en",{"_key":20437,"_type":99,"children":20438,"markDefs":20443,"style":799},"wxKagBwedgJOJbSDoFsET",[20439],{"_key":20440,"_type":103,"marks":20441,"text":20442},"5d9acc9404f5",[],"The Horizon Europe program is aimed at streamlining the EU’s position as a world leader in science. Its ultimate goal is to bring excellent research results to market to deliver direct benefits to citizens, such as affordable health care, protection against cybercrime and the transition to a resource-efficient, low-carbon economy.",[],{"_key":20445,"_type":99,"children":20446,"markDefs":20451,"style":182},"sZWuajynEQiN5uv2JEKK4",[20447],{"_key":20448,"_type":103,"marks":20449,"text":20450},"99ad7074d9df",[],"Project Overview: Advancing Manufacturing",[],{"_key":20453,"_type":99,"children":20454,"markDefs":20459,"style":799},"518BWlwqwEQCNMmuNJ3C0",[20455],{"_key":20456,"_type":103,"marks":20457,"text":20458},"f0d56aef0b20",[],"The FLASH project will focus on “highly customized laser-based production including new and advanced methods to provide a highly precise distribution of photons at the right place and time”. The consortium’s goal is to develop a multi-process laser-machine tool capable of thermal-based (hardening, welding, cutting, macro polishing and drilling of metals and alloys) and ablation-based (texturing, micro-machining/polishing) processes, as well as multi-beam cutting and drilling of advanced, reflective, composite and ceramic materials.",[],{"_key":20461,"_type":99,"children":20462,"markDefs":20467,"style":799},"9tpnbtTHZUrckAz8WiDsa",[20463],{"_key":20464,"_type":103,"marks":20465,"text":20466},"50d4596dbd85",[],"This will be achieved by combining multiple beams that will be deliverable, in any combination, to the delivery systems. It will allow a single versatile machine tool to replace up to three separate machine tools, with full material and process flexibility. In addition, it will deliver an unprecedented level of manufacturing line agility, by enabling the reconfiguration of processes through the automated changeover of the laser beam delivery system in just seconds, compared to the several hours needed to replace or reconfigure traditional mechanical or laser machines. This highly precise type of manufacturing reduces waste, defects and energy consumption, leading to more successful and sustainable products.",[],{"_key":20469,"_type":99,"children":20470,"markDefs":20475,"style":182},"NynX8RppNyqElzZKLsEBe",[20471],{"_key":20472,"_type":103,"marks":20473,"text":20474},"1e33361955d7",[],"Delivering Better Outcomes for Business",[],{"_key":20477,"_type":99,"children":20478,"markDefs":20483,"style":799},"sXz-VYYwkxFPNyIiMwtU2",[20479],{"_key":20480,"_type":103,"marks":20481,"text":20482},"a509101cf9db",[],"The FLASH project will aim to deliver a fully optimized processing strategy for the industry. Considering all processes and parameters available to the FLASH machine platform, the process design package will identify the best sequence of individual processing steps and provide optimized parameters for each (e.g., tool path, power, pulse length, beam shape, spatial coherence, etc.). In contrast with existing modeling solutions, FLASH will deliver predictive capabilities for manufacturing. This will enable non-expert users, including SMEs, to rapidly develop new processes during accelerated product and process development cycles. 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By creating a digital replica of the project, architects and engineers can visualize and simulate different design options, allowing them to identify potential design flaws and optimize the overall structure. This virtual testing and simulation significantly reduce the risk of costly design errors and rework during construction. 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Facility managers can monitor the performance of critical systems, such as HVAC and electrical, and proactively address maintenance needs before they become disruptive. The model also facilitates energy optimization by analyzing the building’s energy consumption patterns, allowing for smarter and more sustainable operation strategies.",[],{"_key":22105,"_type":99,"children":22106,"markDefs":22110,"style":170},"-sKFrBI2roSDmypQNOlBg",[22107],{"_type":103,"marks":22108,"text":22109},[],"Conclusion:",[],{"_key":22112,"_type":99,"children":22113,"markDefs":22117,"style":799},"ldqaBch1hM-60JzBRcpjK",[22114],{"_type":103,"marks":22115,"text":22116},[],"The Digital Twins model is reshaping the construction industry, offering unprecedented opportunities for project management, design, and maintenance. By creating virtual replicas of physical assets, stakeholders can benefit from enhanced visibility, improved collaboration, and optimized decision-making. As the industry embraces this transformative technology, it is crucial for construction professionals to stay ahead of the curve and leverage the power of the Digital Twins model to drive efficiency, reduce costs, and deliver successful projects in a rapidly evolving digital era.",[],{"_key":22119,"_type":99,"children":22120,"markDefs":22137,"style":799},"fE_Rld_PWRNRXkOe23Y_t",[22121,22124,22127,22130,22134],{"_type":103,"marks":22122,"text":22123},[],"Do you want to bring your construction project to the next level? ",{"_type":103,"marks":22125,"text":20869},[22126],"X0OgH4BEjtlxmCgcUfzWE",{"_type":103,"marks":22128,"text":22129},[]," and let us help you! 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This cutting-edge technology",[],"Digital Twins in Healthcare: Revolutionizing Patient Care","digital-twins-in-healthcare","0|1000mw:",[22175],{"_createdAt":22176,"_id":22177,"_key":22178,"_ref":22177,"_rev":22156,"_type":168,"_updatedAt":22176,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":22179,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:21Z","oAJoyTRUXU_UQqnzK_Dlk","AJ7hHWBwmczp4h0b36puC",[22180,22187,22194,22208,22215,22222,22229,22236,22243,22250,22257,22264,22271,22278],{"_key":22181,"_type":99,"children":22182,"markDefs":22186,"style":799},"dCprnod2QuhevdssVeYlm",[22183],{"_type":103,"marks":22184,"text":22185},[],"Digital Twins in Healthcare are transforming the landscape of medical practice, ushering in a new era of personalized and precise patient care. This cutting-edge technology allows healthcare professionals to create virtual replicas of individuals, enabling them to monitor, analyze, and optimize patients’ health in real time. With the potential to revolutionize diagnosis, treatment, and prevention, digital twins are poised to make a significant impact on healthcare outcomes.",[],{"_key":22188,"_type":99,"children":22189,"markDefs":22193,"style":170},"YDua6-3DJ75PkUmsUOWcP",[22190],{"_type":103,"marks":22191,"text":22192},[],"What is a Digital Twin",[],{"_key":22195,"_type":99,"children":22196,"markDefs":22205,"style":799},"uqIAVWBvDSJiA8rL1mlcs",[22197,22200,22203],{"_type":103,"marks":22198,"text":22199},[],"A digital twin is a virtual representation of a patient that mirrors their physical characteristics, physiology, and medical history. By integrating data from various sources such as wearable devices, electronic health records, and genetic profiles, healthcare providers can create a comprehensive and dynamic model of an individual’s health. This digital replica captures the intricacies of a person’s unique biology, enabling healthcare professionals to gain deeper insights and make more informed decisions. However, you can learn more about the concept of Digital Twin in this ",{"_type":103,"marks":22201,"text":72},[22202],"yvzguDJS4ZvUaNl0NXWjZ",{"_type":103,"marks":22204,"text":793},[],[22206],{"_key":22202,"_type":173,"href":22207},"https://cosmosthrace.com/what-are-digital-twins/",{"_key":22209,"_type":99,"children":22210,"markDefs":22214,"style":170},"k7FgW89dbwYR22HAVH-YC",[22211],{"_type":103,"marks":22212,"text":22213},[],"Applications of Digital Twin Models in Healthcare",[],{"_key":22216,"_type":99,"children":22217,"markDefs":22221,"style":170},"UdrxAuzBShUIkuxK-8r6O",[22218],{"_type":103,"marks":22219,"text":22220},[],"Prediction and prevention",[],{"_key":22223,"_type":99,"children":22224,"markDefs":22228,"style":799},"hXnN92Doe7YDgj0t1Wv0L",[22225],{"_type":103,"marks":22226,"text":22227},[],"One of the most significant applications of digital twins in healthcare is in disease prediction and prevention. Therefore, by continuously monitoring a patient’s digital twin, healthcare providers can identify subtle changes in vital signs, biomarkers, and behaviors that may indicate the onset of a disease. This early detection allows for timely intervention, preventing the progression of illnesses and potentially saving lives. Additionally, digital twins can simulate the effects of lifestyle modifications or treatments, helping individuals make informed decisions about their health.",[],{"_key":22230,"_type":99,"children":22231,"markDefs":22235,"style":170},"0Py3_2RUrMD2fpf16Brri",[22232],{"_type":103,"marks":22233,"text":22234},[],"Patient treatment",[],{"_key":22237,"_type":99,"children":22238,"markDefs":22242,"style":799},"aO9Pugi1F1rzq5A008lgE",[22239],{"_type":103,"marks":22240,"text":22241},[],"In the realm of treatment, digital twins provide a platform for precision medicine. With access to comprehensive patient data, healthcare professionals can tailor therapies and medications to individual needs, maximizing efficacy while minimizing adverse effects. The virtual replica can simulate the effects of different interventions, enabling healthcare providers to optimize treatment strategies and predict patient responses. This personalized approach improves treatment outcomes and enhances patient satisfaction.",[],{"_key":22244,"_type":99,"children":22245,"markDefs":22249,"style":170},"QYhL9OmeFQMTWweaKycAH",[22246],{"_type":103,"marks":22247,"text":22248},[],"Surgery planning and training",[],{"_key":22251,"_type":99,"children":22252,"markDefs":22256,"style":799},"o1FszFkOwNfpimos4Klka",[22253],{"_type":103,"marks":22254,"text":22255},[],"Digital twins also play a crucial role in surgical planning and training. By constructing a virtual replica of a patient’s anatomy, surgeons can simulate complex procedures and anticipate potential challenges before stepping into the operating room. This preoperative planning enhances surgical precision, reduces the risk of complications, and shortens recovery times. Moreover, digital twins offer a valuable tool for training healthcare professionals, allowing them to practice and refine their skills in a realistic virtual environment.",[],{"_key":22258,"_type":99,"children":22259,"markDefs":22263,"style":170},"8J0kvjBHgBVOfxzQfeyM9",[22260],{"_type":103,"marks":22261,"text":22262},[],"Analytics of Patients’ Data",[],{"_key":22265,"_type":99,"children":22266,"markDefs":22270,"style":799},"bCBEElcKmTj4mGKDR3viI",[22267],{"_type":103,"marks":22268,"text":22269},[],"The potential of digital twins in healthcare extends beyond individual patient care. These virtual replicas can aggregate anonymized data from multiple patients to generate population-level insights. By analyzing patterns, trends, and responses to various interventions, healthcare researchers can identify novel therapies, optimize healthcare delivery, and develop preventive strategies. Therefore, this data-driven approach has the potential to drive medical advancements and improve public health outcomes.",[],{"_key":22272,"_type":99,"children":22273,"markDefs":22277,"style":799},"FcoGDHTyf8PVPgLI_pJBV",[22274],{"_type":103,"marks":22275,"text":22276},[],"In conclusion, digital twins in healthcare hold immense promise for revolutionizing patient care. By creating virtual replicas that capture the intricacies of an individual’s health, healthcare providers can make more informed decisions, tailor treatments, and improve outcomes. From disease prevention and precision medicine to surgical planning and population health insights, digital twins have the potential to reshape the healthcare landscape. The Digital Twins model has numerous applications in other sectors as well.",[],{"_key":22279,"_type":99,"children":22280,"markDefs":22292,"style":799},"0JjrJHgXDZXikPEfBAz6o",[22281,22284,22287,22290],{"_type":103,"marks":22282,"text":20869},[22283],"8_ay21LiETMcjO1twCgb0",{"_type":103,"marks":22285,"text":22286},[]," if your want to learn more about the different applications of the Digital Twins model! You can also check our full ",{"_type":103,"marks":22288,"text":22133},[22289],"2CZGhb7WY6cENwNowyslO",{"_type":103,"marks":22291,"text":22136},[],[22293,22294],{"_key":22283,"_type":173,"href":19536},{"_key":22289,"_type":173,"href":19377},{"_type":17,"current":22172},[22297,22298],{"_createdAt":17581,"_id":17582,"_rev":17583,"_type":8636,"_updatedAt":17584,"name":17585,"orderRank":17325,"uid":17586},{"_createdAt":22144,"_id":22145,"_rev":22146,"_type":8636,"_updatedAt":22147,"name":22148,"orderRank":15683,"uid":22149},{"_createdAt":22300,"_id":22301,"_rev":22302,"_system":22303,"_type":72,"_updatedAt":22306,"archived":126,"author":161,"category":22307,"date":22311,"description":22312,"image":161,"name":22321,"oldSlug":22322,"orderRank":22323,"reviewer":161,"sections":22324,"seo":161,"slug":22460,"tags":22461},"2026-01-15T22:00:43Z","241518f4-5c40-4e19-91d2-bd8bf7444a8d","2oGVswEwQBfyYUvi8RUVN7",{"base":22304},{"id":22301,"rev":22305},"YkA36qTDOerM1fSJamepN5","2026-01-26T10:39:16Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":22308,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":22310,"uid":66},{"base":22309},{"id":57,"rev":61},{"_type":17,"current":66},"2023-06-16",[22313],{"_key":22314,"_type":99,"children":22315,"markDefs":22320,"style":107},"9c7a81ca1cfd",[22316],{"_key":22317,"_type":103,"marks":22318,"text":22319},"0c6e426b1614",[],"Aleks Milchov has been part of Cosmos Thrace for over a year and a half now. 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His unique and kind personality, talent, and determination make him a vital part of our technical team. Although he is merely twenty-one years old, he has over 3 years of professional programming experience. He is absolute proof that in our area age is just a number and that you should not judge the book by its cover. How the career of this young software engineer is progressing in Cosmos Thrace? Read the rest of the article to find the answer!",[],{"_key":22338,"_type":99,"children":22339,"markDefs":22343,"style":170},"lBpF95tJCofoOPLa9XVVm",[22340],{"_type":103,"marks":22341,"text":22342},[],"How did his Cosmos Thrace adventure start?",[],{"_key":22345,"_type":99,"children":22346,"markDefs":22350,"style":799},"-AagzjUkqCqKVHelOZ0WD",[22347],{"_type":103,"marks":22348,"text":22349},[],"Almost a couple of years ago Aleks was still in high school while also working professionally as a software engineer in a big IT corporation. However, he was looking for a new challenge in his career. A challenge that would give him the opportunity to grow not only in terms of technical skills but also in terms of soft and managerial skills.",[],{"_key":22352,"_type":99,"children":22353,"markDefs":22357,"style":799},"mTkC_apuJKndI0DGVJ_7x",[22354],{"_type":103,"marks":22355,"text":22356},[],"He stumbled upon a job opening from Cosmos Thrace for a Business Intelligence specialist and applied. After an interview with Viktor Elevterov, the CEO of Cosmos Thrace, it was clear that Aleks was a perfect match for the young and ambitious team of Cosmos Thrace. However, he first started as a React Developer for a software development project within the company.",[],{"_key":22359,"_type":99,"children":22360,"markDefs":22364,"style":170},"bVPcrJZXbv7FqfiLdaWDp",[22361],{"_type":103,"marks":22362,"text":22363},[],"How is his Cosmos Thrace adventure continuing?",[],{"_key":22366,"_type":99,"children":22367,"markDefs":22371,"style":799},"tdoJB9AdZfnro6ZunCjku",[22368],{"_type":103,"marks":22369,"text":22370},[],"After a few months, Aleks joined another project for a US client of the company. His role was of an implementation specialist. This differed from his past position, however, it enabled him to expand and diversify his skills and knowledge. Currently, he is leading a project for another client of Cosmos Thrace, where a Business Intelligence platform is being developed. ",[],{"_key":22373,"_type":99,"children":22374,"markDefs":22387,"style":799},"rrjdVtLZ2wVO0zjTy0Gb1",[22375,22378,22381,22384],{"_type":103,"marks":22376,"text":22377},[],"When asked about the things that Aleks likes the most in Cosmos Thrace, his top reason is the people within the company.",{"_type":103,"marks":22379,"text":22380},[],"“",{"_type":103,"marks":22382,"text":22383},[14153],"I like the people and the atmosphere a lot. We have versatile professionals in the company and we can all learn from each other’s skills. The biggest benefit is that we are really supportive of each other – whenever I have a difficulty there is someone I can rely on and assist me. This start-up vibe is what makes me love the company",{"_type":103,"marks":22385,"text":22386},[],".”",[],{"_key":22389,"_type":99,"children":22390,"markDefs":22394,"style":170},"kZuDDWP1YGmZUpSbMuBte",[22391],{"_type":103,"marks":22392,"text":22393},[],"How will the adventure continue?",[],{"_key":22396,"_type":99,"children":22397,"markDefs":22401,"style":799},"Qk3T6Qv2P7NPM30CyswTF",[22398],{"_type":103,"marks":22399,"text":22400},[],"Aleks mentions that he sees a big difference compared to his last company and Cosmos Thrace. This difference is presented in the less stressful and chill internal order within the company:",[],{"_key":22403,"_type":99,"children":22404,"markDefs":22408,"style":799},"uJFZ3H3oT8CVso9RUY9ae",[22405],{"_type":103,"marks":22406,"text":22407},[14153],"“My former company was a big corporation and the hierarchical order was very strict and well-established. I had one person above me to whom I had to report and look for support. However, in Cosmos Thrace, I am able to communicate freely with everyone. Moreover, my work and contribution are well more appreciated here. This motivates me to keep working and developing my professional skills.”",[],{"_key":22410,"_type":99,"children":22411,"markDefs":22420,"style":799},"IyZfJupP21mN0y1KYVOAs",[22412,22415,22418],{"_type":103,"marks":22413,"text":22414},[],"Therefore, he sees himself playing a key role for Cosmos Thrace in the next few years. Nevertheless, he feels that he can contribute even more by turning his sight a bit from strictly technical tasks and focusing on managerial duties.",{"_type":103,"marks":22416,"text":22417},[14153],"“I want to shift my focus a bit on management. I want to be a team leader and be able to manage the people on the team. My philosophy is that good management skills can make employees independent and can easily progress in their careers and then be supportive of new employees. In Cosmos Thrace, I have the freedom to go after that opportunity and growth path”",{"_type":103,"marks":22419,"text":793},[],[],{"_key":22422,"_type":99,"children":22423,"markDefs":22427,"style":170},"Xe5ZwFI_FAleddZyuypF5",[22424],{"_type":103,"marks":22425,"text":22426},[],"Work hard, play hard",[],{"_key":22429,"_type":99,"children":22430,"markDefs":22437,"style":799},"JO47wpymo62HLeiGqtGC5",[22431,22434],{"_type":103,"marks":22432,"text":22433},[],"Being one of the funniest guys in the company, Aleks is always in for a party or a weekend barbeque. During team-building activities of the company, he is always the one to look out for. His endless positive energy and desire for good times are qualities that make everyone enjoy his company.",{"_type":103,"marks":22435,"text":22436},[],"Therefore, at the end of his interview, we asked him to tell a memorable story that he remembers since joining Cosmos Thrace:",[],{"_key":22439,"_type":99,"children":22440,"markDefs":22444,"style":799},"MQDTvRJpKkXgQevRsTtbb",[22441],{"_type":103,"marks":22442,"text":22443},[14153],"“The situation I remember best is when, at one of the team building events organized by the company, we talked about the technologies that everyone is familiar with. However, I was just brought into a new project. During the teambuilding, we discussed my upcoming onboarding in the project with the company’s managerial team in a chill and friendly atmosphere and paved the path forward. That’s the beauty of Cosmos Thrace. We are all united and make our decisions together.”",[],{"_key":22446,"_type":99,"children":22447,"markDefs":22458,"style":799},"gUZyCbV45ECGaiLL3Y6eG",[22448,22451,22455],{"_type":103,"marks":22449,"text":22450},[],"Are you a young software engineer looking to bring your career to the next level? Check our ",{"_type":103,"marks":22452,"text":22454},[22453],"kBk_WdJRwUin5JvKZEzvv","open positions",{"_type":103,"marks":22456,"text":22457},[]," and find your next dream job!",[22459],{"_key":22453,"_type":173,"href":20182},{"_type":17,"current":22322},[22462],{"_createdAt":22463,"_id":22464,"_rev":22465,"_type":8636,"_updatedAt":22466,"name":22467,"orderRank":22468,"uid":22469},"2026-01-20T12:48:07Z","aacb1946-5095-430b-887c-f14d07458964","8sLbU849Ngr6bwLlc9qOPn","2026-01-20T12:48:11Z","Our Stories","0|1000d4:","our-stories",{"_createdAt":22471,"_id":22472,"_rev":22473,"_system":22474,"_type":72,"_updatedAt":22477,"archived":126,"author":161,"category":22478,"date":22482,"description":22483,"image":161,"name":22492,"oldSlug":22493,"orderRank":22494,"reviewer":161,"sections":22495,"seo":161,"slug":22762,"tags":22763},"2026-01-15T16:18:18Z","4879c2fe-7faa-4945-89c9-2cc762c9d59f","ir9xdmjsDvNqVMLz9Xxw8M",{"base":22475},{"id":22472,"rev":22476},"3x1HJiv3wwU7cYVoHu7GQI","2026-01-28T09:54:40Z",{"_createdAt":32,"_id":33,"_rev":34,"_system":22479,"_type":12,"_updatedAt":38,"name":39,"orderRank":40,"slug":22481,"uid":42},{"base":22480},{"id":33,"rev":37},{"_type":17,"current":42},"2023-06-07",[22484],{"_key":22485,"_type":99,"children":22486,"markDefs":22491,"style":107},"9ed5f34ba646",[22487],{"_key":22488,"_type":103,"marks":22489,"text":22490},"ecaec6956090",[],"The first steps of every new challenge can often seem difficult and confusing. The purpose of this article is to serve as a guide to...",[],"A guide to Power BI reporting","a-guide-to-power-bi-reporting","0|1000t4:",[22496],{"_createdAt":22497,"_id":22498,"_key":22499,"_ref":22498,"_rev":22500,"_type":168,"_updatedAt":22497,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":22501,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:50:12Z","Gpk2yhsLcIBYSk2YM2VbR","9qM9K7EEnQ4O7zL9so2fC","ZfaOePOqVJD5r4KHzTaYKv",[22502,22509,22516,22531,22538,22545,22552,22559,22566,22582,22598,22608,22618,22628,22638,22648,22655,22662,22669,22676,22683,22690,22696,22703,22710,22717,22724,22731,22738],{"_key":22503,"_type":99,"children":22504,"markDefs":22508,"style":799},"Cmm0FVAxx_2Zm0gmILn25",[22505],{"_type":103,"marks":22506,"text":22507},[],"The first steps of every new challenge can often seem difficult and confusing. The purpose of this article is to serve as a guide to power BI reporting. Through it, we hope that new and aspiring BI specialists will be able to navigate  Power BI more easily. Read it for insights to help you build your first report in minutes!",[],{"_key":22510,"_type":99,"children":22511,"markDefs":22515,"style":170},"U450jiXs2ZVIBAwkJsOyu",[22512],{"_type":103,"marks":22513,"text":22514},[],"Power BI: An overview",[],{"_key":22517,"_type":99,"children":22518,"markDefs":22528,"style":799},"_NluZKwENmdjyd-3yt-Yc",[22519,22522,22525],{"_type":103,"marks":22520,"text":22521},[],"Power BI is a business intelligence tool that allows you to generate useful insights based on your data in the form of reports and dashboards. It is a Microsoft product and has a number of interesting features such as supporting various data formats, being able to connect different data sources and powerful visualization formats. You can read a more detailed overview of the platform in this ",{"_type":103,"marks":22523,"text":72},[22524],"GT-AaiVDxYsJw-m3rGmow",{"_type":103,"marks":22526,"text":22527},[],". ",[22529],{"_key":22524,"_type":173,"href":22530},"https://cosmosthrace.com/what-is-microsoft-power-bi-reporting/",{"_key":22532,"_type":99,"children":22533,"markDefs":22537,"style":799},"ikZTodxm2QbxLTgRRTW_B",[22534],{"_type":103,"marks":22535,"text":22536},[],"For the purpose of this article, it should be mentioned that Power BI has three main elements:",[],{"_key":22539,"_type":99,"children":22540,"level":230,"listItem":231,"markDefs":22544,"style":107},"4W1wfsEpD-u9oUSiFMRFX",[22541],{"_type":103,"marks":22542,"text":22543},[],"Power BI Desktop: The main application of Power BI Desktop is to build and design reports",[],{"_key":22546,"_type":99,"children":22547,"level":230,"listItem":231,"markDefs":22551,"style":107},"H7Me1jkV94zElVWIcS5my",[22548],{"_type":103,"marks":22549,"text":22550},[],"Power BI Service: Through Power BI Service you can share reports and build dashboards",[],{"_key":22553,"_type":99,"children":22554,"level":230,"listItem":231,"markDefs":22558,"style":107},"1kaEkbQGA0-GFQt3X9QCP",[22555],{"_type":103,"marks":22556,"text":22557},[],"Power BI Mobile App: Used for viewing reports and dashboards with your mobile phone.",[],{"_key":22560,"_type":99,"children":22561,"markDefs":22565,"style":170},"SFblySx9AE9NnbwQWC5vN",[22562],{"_type":103,"marks":22563,"text":22564},[],"The components of Power BI Desktop",[],{"_key":22567,"_type":99,"children":22568,"markDefs":22579,"style":799},"jq77A0WC-olSLT7stZ1on",[22569,22572,22576],{"_type":103,"marks":22570,"text":22571},[],"As stated above, Power BI Desktop is the element of Power BI that enables report generation and design. We recommend downloading the app from the official Microsoft ",{"_type":103,"marks":22573,"text":22575},[22574],"PtsSvJpY_N-4Cw9y2kvmX","website",{"_type":103,"marks":22577,"text":22578},[]," and installing it according to the specified steps. ",[22580],{"_key":22574,"_type":173,"href":22581},"https://powerbi.microsoft.com/en-gb/desktop/",{"_key":22583,"_type":99,"children":22584,"markDefs":22595,"style":799},"Fwf9lXzs7h-daJuX4Rb3r",[22585,22588,22592],{"_type":103,"marks":22586,"text":22587},[],"Upon launching Power BI Desktop, a blank report will appear. Around the blank canvas you will find a few important ",{"_type":103,"marks":22589,"text":22591},[22590],"dG5umQC80OrgTWtFtfr3K","components",{"_type":103,"marks":22593,"text":22594},[]," that deserve a mention:",[22596],{"_key":22590,"_type":173,"href":22597},"https://www.datacamp.com/tutorial/tutorial-power-bi-for-beginners",{"_key":22599,"_type":99,"children":22600,"level":230,"listItem":231,"markDefs":22607,"style":107},"xhRlBFjwb56owV0zUSWFZ",[22601,22604],{"_type":103,"marks":22602,"text":22603},[3055],"Top Ribbon",{"_type":103,"marks":22605,"text":22606},[]," – This is where most of the controls and options that you need to build a report are located",[],{"_key":22609,"_type":99,"children":22610,"level":230,"listItem":231,"markDefs":22617,"style":107},"Wc19BGj8mNcUTyMivkaKS",[22611,22614],{"_type":103,"marks":22612,"text":22613},[3055],"Views",{"_type":103,"marks":22615,"text":22616},[]," – This is made up of the report view, the data view and the model view.",[],{"_key":22619,"_type":99,"children":22620,"level":230,"listItem":231,"markDefs":22627,"style":107},"2PoqY1WnDvAiK2g1bsgLn",[22621,22624],{"_type":103,"marks":22622,"text":22623},[3055],"Filters",{"_type":103,"marks":22625,"text":22626},[]," – From here you can select different options for filtering the data.",[],{"_key":22629,"_type":99,"children":22630,"level":230,"listItem":231,"markDefs":22637,"style":107},"On6YAPoUS5iRE-0ZHsR_E",[22631,22634],{"_type":103,"marks":22632,"text":22633},[3055],"Visualizations",{"_type":103,"marks":22635,"text":22636},[]," – One of the most interesting components of the app, this contains all the possible options for visually representing your data.",[],{"_key":22639,"_type":99,"children":22640,"level":230,"listItem":231,"markDefs":22647,"style":107},"oKGLoU8j-L2q2lntR63ef",[22641,22644],{"_type":103,"marks":22642,"text":22643},[3055],"Fields",{"_type":103,"marks":22645,"text":22646},[]," – This section contains the tables and fields that are available in the data model.",[],{"_key":22649,"_type":99,"children":22650,"markDefs":22654,"style":170},"o2dKZECFJO9BfhC51EqGr",[22651],{"_type":103,"marks":22652,"text":22653},[],"Key steps to generating a Power BI Report",[],{"_key":22656,"_type":99,"children":22657,"markDefs":22661,"style":799},"j2MY4vJOuNkucPDpkP0l-",[22658],{"_type":103,"marks":22659,"text":22660},[],"Now that you know which element of Power BI you need for generating a report, let’s break the whole process down into a couple of simple steps. In the following lines you will see our guide to Power BI reporting.",[],{"_key":22663,"_type":99,"children":22664,"markDefs":22668,"style":170},"SOwArsK09F2dkgS8PWLI7",[22665],{"_type":103,"marks":22666,"text":22667},[],"Importing data into Power BI and supported data sources",[],{"_key":22670,"_type":99,"children":22671,"markDefs":22675,"style":799},"GKlZ9sBz3sgOwAKE_iCvV",[22672],{"_type":103,"marks":22673,"text":22674},[],"The first step when creating a report is to import the data that will construct it. You already know that Power BI enables you to connect data from various data sources. Those can be Excel files, CSV files, SQL Databases, SharePoint lists and many more. Once you have the data on your device, you can easily import it into the app. If, for example, you import an Excel file, upon importing it, you will be able to select whether to proceed with the whole file, a table, a sheet and so on. During that process you will also have the option to directly import or transform the data first, using Power Query. ",[],{"_key":22677,"_type":99,"children":22678,"markDefs":22682,"style":170},"WSxQOF3ek1lW_iVwABY-_",[22679],{"_type":103,"marks":22680,"text":22681},[],"Data modeling and navigation",[],{"_key":22684,"_type":99,"children":22685,"markDefs":22689,"style":799},"gOT-S3ZYw0GYYl01qnG2j",[22686],{"_type":103,"marks":22687,"text":22688},[],"The next step of the process is to model the data that you have imported and establish relationships. Those relationships enable you to connect data from different sources. Data modeling is one of the most powerful features of Power BI Desktop. Through it, you can create custom calculations based on the data sets that have been imported. You can then visualize those calculations in an interesting and meaningful way. ",[],{"_key":22691,"_type":99,"children":22692,"markDefs":22695,"style":170},"WDZeMtF5JVYM8hXQvYJTg",[22693],{"_type":103,"marks":22694,"text":19333},[],[],{"_key":22697,"_type":99,"children":22698,"markDefs":22702,"style":799},"zDB_y2zz43lcatgW3sU__",[22699],{"_type":103,"marks":22700,"text":22701},[],"Once you have established relationships between different data sets and created calculations, it is time to visualize the data in an organized and attractive way. As mentioned above, Power BI Desktop gives you the ability to visualize data through a variety of options. For example, you can use bar charts, line charts, pie charts, tables, cards, interactive maps, etc. This powerful feature of the app is what makes it stand out from the rest. You can even create your own visualizations, if you have some programming experience. ",[],{"_key":22704,"_type":99,"children":22705,"markDefs":22709,"style":799},"WQNXrDa728NK2qcGimVXT",[22706],{"_type":103,"marks":22707,"text":22708},[],"Afterward, you just need to do some styling and design in order for your reports to look good and be easy to read. Although this looks like a simple step, it is often overlooked by professionals,  making their reports unattractive and often unreadable. ",[],{"_key":22711,"_type":99,"children":22712,"markDefs":22716,"style":170},"8VVJ0HxMC6hDpy-VsQlEG",[22713],{"_type":103,"marks":22714,"text":22715},[],"Publishing reports",[],{"_key":22718,"_type":99,"children":22719,"markDefs":22723,"style":799},"6iRKB4QB8-Dfs3hR_QDlF",[22720],{"_type":103,"marks":22721,"text":22722},[],"The final step of the process is publishing the report to your Power BI Workspace. Keep in mind that once the report is published it can be found on Power BI Service. Moreover, publishing the reports also publishes the data related to that report. ",[],{"_key":22725,"_type":99,"children":22726,"markDefs":22730,"style":170},"dTFDFxUHqqpo1j_kSUFFY",[22727],{"_type":103,"marks":22728,"text":22729},[],"Gaining a competitive edge with Power BI",[],{"_key":22732,"_type":99,"children":22733,"markDefs":22737,"style":799},"Ege-pXOzMN1W71t7MEE6i",[22734],{"_type":103,"marks":22735,"text":22736},[],"Getting useful insights from the data that your business generates is crucial in today’s business world. It can give you the competitive advantage to stand out from your competitors and optimize your operations. To achieve this, effective and comprehensive reporting and analytics of that data are required. Power BI gives you the ability to build meaningful reports in a few very easy and accessible steps. We hope that this guide to Power Bi reporting will enable you to make use of it today!",[],{"_key":22739,"_type":99,"children":22740,"markDefs":22758,"style":799},"q9G4d9qKgOusriMolvS4J",[22741,22744,22748,22751,22755],{"_type":103,"marks":22742,"text":22743},[],"For more insights on how to maximize Power BI, ",{"_type":103,"marks":22745,"text":22747},[22746],"GtSXcNUoOqhdmnEWfbGEJ","view our other articles",{"_type":103,"marks":22749,"text":22750},[]," on the topic. You can also ",{"_type":103,"marks":22752,"text":22754},[22753],"78d1Mfuj6Dp99UStydWoJ","schedule",{"_type":103,"marks":22756,"text":22757},[]," a free call and let us help you start your digital transformation journey!",[22759,22761],{"_key":22746,"_type":173,"href":22760},"https://cosmosthrace.com/data-and-ai-resources/",{"_key":22753,"_type":173,"href":19536},{"_type":17,"current":22493},[22764,22765],{"_createdAt":19381,"_id":19382,"_rev":19383,"_type":8636,"_updatedAt":19384,"name":19385,"orderRank":10508,"uid":19386},{"_createdAt":12143,"_id":12144,"_rev":12145,"_type":8636,"_updatedAt":12146,"name":12147,"orderRank":12148,"uid":12149},{"_createdAt":22767,"_id":22768,"_rev":22769,"_system":22770,"_type":72,"_updatedAt":22773,"archived":126,"author":161,"category":22774,"date":22778,"description":22779,"image":161,"name":22788,"oldSlug":22789,"orderRank":22468,"reviewer":161,"sections":22790,"seo":161,"slug":22910,"tags":22911},"2026-01-15T15:52:36Z","0bb31974-9bf8-4c3e-83dc-fd71d803d1d7","6vWVb2JzOLlINiPQfMiKYU",{"base":22771},{"id":22768,"rev":22772},"ZfaOePOqVJD5r4KHzTTHIz","2026-01-28T09:57:21Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":22775,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":22777,"uid":30},{"base":22776},{"id":21,"rev":25},{"_type":17,"current":30},"2023-05-12",[22780],{"_key":22781,"_type":99,"children":22782,"markDefs":22787,"style":107},"13f33aaf7d79",[22783],{"_key":22784,"_type":103,"marks":22785,"text":22786},"392f57a36e04",[],"Many business owners try to figure out how to apply digital transformation amid all the buzz about it.",[],"Should You Consider Digital Transformation as a Way to Gain Competitive Advantage?","should-you-consider-digital-transformation-as-a-way-to-gain-competitive-advantage",[22791],{"_createdAt":22792,"_id":22793,"_key":22794,"_ref":22793,"_rev":22772,"_type":168,"_updatedAt":22792,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":22795,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:35Z","RXNr52PhZziqtUVmeanuu","xX-V9dNxc57tqNrFtto0X",[22796,22829,22836,22843,22850,22857,22876,22886,22896,22903],{"_key":22797,"_type":99,"children":22798,"markDefs":22822,"style":799},"9lWL1M0sD-nQXjbgjunOU",[22799,22802,22805,22808,22812,22815,22819],{"_type":103,"marks":22800,"text":22801},[],"Many business owners try to figure out how to apply digital transformation amid all the buzz about it. It can take numerous shapes from online payment to labor automation, encompassing concepts like ",{"_type":103,"marks":22803,"text":22148},[22804],"UsZ_KE4l3jmaoUcS7NVbx",{"_type":103,"marks":22806,"text":22807},[],", ",{"_type":103,"marks":22809,"text":22811},[22810],"5XU8UjLatNmzEDZOQV16e","Predictive Maintenance",{"_type":103,"marks":22813,"text":22814},[]," and ",{"_type":103,"marks":22816,"text":22818},[22817],"IMh-yerC-kUxo5eSCNcou","Digital twins",{"_type":103,"marks":22820,"text":22821},[],". 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The capacity to design solutions for efficiency improvement is the clearest illustration of how digital transformation provides a competitive advantage. One does not have to be a manufacturer to see the value in using digital technology to improve operations and harvest the benefits of greater process structures.  ",[],{"_key":22844,"_type":99,"children":22845,"markDefs":22849,"style":799},"8mxIpC-bp8RrGaJk5hGL-",[22846],{"_type":103,"marks":22847,"text":22848},[],"For example, an AI-based tool for translating voicemail to text will improve the company’s administrative function, enhancing overall efficiency. Furthermore, even simple digitalization of sales procedures saves time and resources for the sales force, which only then can be fully focused on building customer relationships.",[],{"_key":22851,"_type":99,"children":22852,"markDefs":22856,"style":170},"MoPwhFxubox3L3QBTxzSk",[22853],{"_type":103,"marks":22854,"text":22855},[],"The benefits of Digital Transformation:",[],{"_key":22858,"_type":99,"children":22859,"level":230,"listItem":4889,"markDefs":22873,"style":107},"N4XZaULjWTF00E2KWfGr6",[22860,22863,22866,22870],{"_type":103,"marks":22861,"text":22862},[],"Increased customer satisfaction:",{"_type":103,"marks":22864,"text":22865},[],"Providing a good customer experience is the best approach to appeal to consumer loyalty. According to a ",{"_type":103,"marks":22867,"text":22869},[22868],"HkTslruUYLRIT4VN2zOGk","PWC survey",{"_type":103,"marks":22871,"text":22872},[],", more satisfied customers demonstrate a higher tendency to pay more for services and products. Actually, a company can make its customers happier by providing a platform for customers to share their feedback. Buyers worldwide are accustomed to using digital devices to manage the bulk of their lives. As a result, a business having a digital presence is more than essential. It is a must that allows the company to communicate with its target audience. Furthermore, big data adoption may assist businesses in better understanding their consumers and delivering the best possible service to them.",[22874],{"_key":22868,"_type":173,"href":22875},"https://www.pwc.com/future-of-cx",{"_key":22877,"_type":99,"children":22878,"level":230,"listItem":4889,"markDefs":22885,"style":107},"LAMp55ODj9scf_gCOQy-u",[22879,22882],{"_type":103,"marks":22880,"text":22881},[],"Improved company efficiency:",{"_type":103,"marks":22883,"text":22884},[],"Employees are the lifeblood of a business. Creating a well-optimized and progressive working environment would immediately lead to improved performance. 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By removing constraints such as location and time, a digital implementation may provide companies with attainable prospects, which before seemed to be impossible. Business owners can find new partners and markets in other countries due to digital transformation.",[],{"_key":22897,"_type":99,"children":22898,"markDefs":22902,"style":170},"MHiQq8ej-0LcbFSfAba0P",[22899],{"_type":103,"marks":22900,"text":22901},[],"The way forward",[],{"_key":22904,"_type":99,"children":22905,"markDefs":22909,"style":799},"JYB6fmttHbqf-v7SMhQUR",[22906],{"_type":103,"marks":22907,"text":22908},[],"There is a significant tendency among businesses to incorporate technology to increase efficiency, productivity, and future opportunities. Almost every young company and startup design their business strategy from a technical aspect. 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His background and experience",[],"Can a Rock and Roll Star be a Junior Python Developer?","can-a-rock-and-roll-star-be-a-junior-python-developer","0|1000u0:",[22946],{"_createdAt":22947,"_id":22948,"_key":22949,"_ref":22948,"_rev":22926,"_type":168,"_updatedAt":22947,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":22950,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:45:13Z","77-wPXwKFQJXDgnBzeCIf","VdbDghkG0OLrGpwe70wTG",[22951,22958,22965,22972,22979,22986,22993,23000,23007,23014,23021,23028,23035,23042,23049,23056,23063,23070],{"_key":22952,"_type":99,"children":22953,"markDefs":22957,"style":799},"8_M7SKlNBA7hyB6EHRtN7",[22954],{"_type":103,"marks":22955,"text":22956},[],"Martin Dimitrov has been in Cosmos Thrace for almost two years and proved to be a unique part of our team. His background and experience might at first sight seem not inline with the background of a typical junior Python developer but that is what makes him stand out of the crowd. ",[],{"_key":22959,"_type":99,"children":22960,"markDefs":22964,"style":799},"SSHRgR1qXZsXSxkCyWUma",[22961],{"_type":103,"marks":22962,"text":22963},[],"His ability to commit himself to delivering the best result possible and make everyone in the room laugh have positioned him as one of the most important team members within the company. Moreover, almost two years later Martin and the company are both developing with the same speed and determination.",[],{"_key":22966,"_type":99,"children":22967,"markDefs":22971,"style":170},"dIvSW08pBM8RzerGKxffu",[22968],{"_type":103,"marks":22969,"text":22970},[],"The journey to becoming part of Cosmos Thrace",[],{"_key":22973,"_type":99,"children":22974,"markDefs":22978,"style":799},"EtHhEmczXiEq17KWR_EqV",[22975],{"_type":103,"marks":22976,"text":22977},[],"“I have played guitar for nearly 10 years and after COVID-19 hit I was wondering what else to do. I decided to enroll in a free course on programming fundamentals and try it out. I haven’t had any passion about it before I started so I just wanted to experiment with it. I started to gain a little bit of knowledge after a few weeks and my interest started to grow. I like it so much that I did it non-stop for 6 months straight for around 20 hours per day.”",[],{"_key":22980,"_type":99,"children":22981,"markDefs":22985,"style":799},"i_NLTRoB9SSmocfG_04JP",[22982],{"_type":103,"marks":22983,"text":22984},[],"At that moment Martin enrolled into two more programming courses that were building on the fundamentals. Although his schedule became quite busy, he was attending all the lectures and completing all the homeworks properly. At that moment, the head lecturer who was overseeing both courses decided to contact Martin and offer him a job opportunity. ",[],{"_key":22987,"_type":99,"children":22988,"markDefs":22992,"style":799},"aXXMaYHQAEEarpsPjcdyl",[22989],{"_type":103,"marks":22990,"text":22991},[],"The lecturer connected Martin and Viktor Elevterov with each other. Viktor interviewed Martin, liked his attitude and determination and decided to offer him a job as Junior Python Developer at Cosmos Thrace. ",[],{"_key":22994,"_type":99,"children":22995,"markDefs":22999,"style":799},"ja6ZVNDAvWpQWKRv_Iub1",[22996],{"_type":103,"marks":22997,"text":22998},[],"This was a pivotal moment for Martin and as he explains:",[],{"_key":23001,"_type":99,"children":23002,"markDefs":23006,"style":799},"6K-iq4sANbuQEjVJo84Nj",[23003],{"_type":103,"marks":23004,"text":23005},[],"“At the beginning I was scared because during my studies I have done some abstract exercises but not real-world cases. That frightened me a bit but I started anyway. While working for Cosmos I also continued with my studies. So 1 year later I am still here and love it!”  ",[],{"_key":23008,"_type":99,"children":23009,"markDefs":23013,"style":170},"ovWalZncanYLRbBe8H-Vz",[23010],{"_type":103,"marks":23011,"text":23012},[],"The current working environment in Cosmos Thrace",[],{"_key":23015,"_type":99,"children":23016,"markDefs":23020,"style":799},"5foKyXmfSrahoP0_e1TAF",[23017],{"_type":103,"marks":23018,"text":23019},[],"“I love the atmosphere here! Everybody is trying to help each other and the company. All the people are working really hard and it may sound like a cliche but it doesn’t feel like working. I am enjoying it. Yeah, sometimes there is a rush and pressure but it is part of the game. Moreover, I feel like as the company grows I am growing with it as well.”",[],{"_key":23022,"_type":99,"children":23023,"markDefs":23027,"style":799},"sPEtrvp5QJ3xi1vWiZkgD",[23024],{"_type":103,"marks":23025,"text":23026},[],"That is how Martin sums up the current working environment within Cosmos Thrace. For him as a junior python developer at the beginning of his career it was very important to have someone to rely on whenever he faced a challenge. Also, he needed people who were not there only to tell him what to do but to push him into finding solutions on his own. In Cosmos Thrace he found the perfect mix of both and looks forward to becoming even more knowledgeable and independent in the future.",[],{"_key":23029,"_type":99,"children":23030,"markDefs":23034,"style":170},"zt1kxJTK-pqNe4Pe-gLjk",[23031],{"_type":103,"marks":23032,"text":23033},[],"The future ahead",[],{"_key":23036,"_type":99,"children":23037,"markDefs":23041,"style":799},"JzmRtm_48iU_Bg_rQopf3",[23038],{"_type":103,"marks":23039,"text":23040},[],"“I definitely see myself staying at Cosmos Thrace for the next few years! I have also discussed that with Viktor. I really appreciate everything that the company has done for me – I had basically zero practical experience and Cosmos Thrace hired me and gave me the opportunity to grow and develop. I am very grateful for that.”",[],{"_key":23043,"_type":99,"children":23044,"markDefs":23048,"style":799},"QnrY1x-eA48btK-oM1r62",[23045],{"_type":103,"marks":23046,"text":23047},[],"At the moment Martin tries out different areas of programming by participating in various projects. His main goal is to develop his generic knowledge and skills in programming and afterwards to specilise in a concrete area. 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I am also experimenting with different genres such as jazz and classical music.”",[],{"_key":23064,"_type":99,"children":23065,"markDefs":23069,"style":799},"7suo1C0L9geGNDgXnXY25",[23066],{"_type":103,"marks":23067,"text":23068},[],"Yeah, as you can see “It’s a long way to the top, if you wanna rock and roll”. Although Martin was faced with a lot of challenges and uncertainties when Covid hit, he managed to make the best of it – start a professional career as a python developer and in his free time do what he loves the most – play guitar and live the rockstar life!",[],{"_key":23071,"_type":99,"children":23072,"markDefs":23090,"style":799},"fIWDIh6IS0HLMV1V__pPY",[23073,23076,23079,23082,23085,23088],{"_type":103,"marks":23074,"text":23075},[],"Do you want to learn more about our open positions? 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He did a master’s in management technology and Economics in Zurich. While working on his thesis, the Covid wave hit, which made him stay in Bulgaria for a while.",[],{"_key":23323,"_type":99,"children":23324,"markDefs":23329,"style":107},"dc85d8b706b0",[23325],{"_key":23326,"_type":103,"marks":23327,"text":23328},"26e70ee97910",[],"That is how it all started. Stuck in Bulgaria, Ivan met Viktor Elevterov, the founder of Cosmos Thrace. Viktor started telling him his ideas and that he wanted to create a company that provides AI and ML services. They instantly felt the formation of the perfect fit as Ivan had the experience and background Viktor was searching for. 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Some claim it has more to do with the visual component, some with the analytical, and yet others with just the attempt to access their data. In fact, the genuine answer to the definition has less to do with technology and more to do with the end goal: how can a company reinvent itself and start making more data-driven decisions? What is the future of business with business intelligence?",[],{"_key":23436,"_type":99,"children":23437,"markDefs":23441,"style":170},"HaYLwKuji16QFFAUt5yrO",[23438],{"_type":103,"marks":23439,"text":23440},[],"Business intelligence is more than a reporting tool or platform. It is a business strategy that allows a company to act and make choices more quickly.",[],{"_key":23443,"_type":99,"children":23444,"markDefs":23448,"style":799},"mrGOE7OA8eOqDB_gT49z3",[23445],{"_type":103,"marks":23446,"text":23447},[],"The quantity of various sources from which data is taken is the most common difficulty encountered when it comes to reporting and analyzing data. Depending on the reasoning and source, data may be in a single database, human labor-intensive Excel files, or a more EDW-type platform, resulting in a variety of solutions to the same query. Nothing is more frustrating than entering a meeting with data you believe is right only to discover that someone else has different answers to the same question. So, how can we solve this issue?",[],{"_key":23450,"_type":99,"children":23451,"markDefs":23455,"style":170},"iOjECrG9Dql5dEcXpl_70",[23452],{"_type":103,"marks":23453,"text":23454},[],"Database architecture is just as much an art as a dashboard design.",[],{"_key":23457,"_type":99,"children":23458,"markDefs":23462,"style":799},"yE2TWsYGN7pHD3tZuZtWs",[23459],{"_type":103,"marks":23460,"text":23461},[],"An entire system can lock up due to a single improper joint between two important tables. If a table has too many columns, it may become useless in the future. 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The ideal situation is for a company to employ a strategy in which IT opens data to analytics teams, who are then enabled to construct powerful visual dashboards with the help of business users. This can only be done when a company first considers the whole operations that stand behind the company.",[],{"_key":23471,"_type":99,"children":23472,"markDefs":23476,"style":799},"s3Jt8EQnoV1NXKOUpc3xE",[23473],{"_type":103,"marks":23474,"text":23475},[],"The most crucial stage in integrating BI in an organization is to assess not only the present architecture but also how people interact with data. A DBA could poll individuals to determine what metrics matter the most to them and what sorts of decisions they are making with the data. All of this data will aid a business intelligence architect in making the best possible selections about the sort of platform that an organization requires.",[],{"_key":23478,"_type":99,"children":23479,"markDefs":23483,"style":170},"TPMq9c-2Pw7jtoCoOzAxm",[23480],{"_type":103,"marks":23481,"text":23482},[],"The next stage in a Business Intelligence journey is to learn more about the types of platforms that might be used inside a company.",[],{"_key":23485,"_type":99,"children":23486,"markDefs":23495,"style":799},"GxQwC-btoNvCjtGuYM68t",[23487,23490,23493],{"_type":103,"marks":23488,"text":23489},[],"When it comes to Business Intelligence, each firm will have specific, “tailored-made” requirements. Some businesses are heavily data-driven and just want assistance in integrating the entire platform with a powerful visualization tool. Some people have no notion of what to do with their data and are working on a tight budget. Then the large corporations are always seeking to innovate and position themselves above their competitors. For each sort of requirement, there are multiple tactics and platforms. We love to deliver custom data solutions so check out our ",{"_type":103,"marks":23491,"text":19370},[23492],"WkxyMy15smu3D1wZ9SwG5",{"_type":103,"marks":23494,"text":20179},[],[23496],{"_key":23492,"_type":173,"href":19377},{"_key":23498,"_type":99,"children":23499,"markDefs":23503,"style":799},"EOe1w-7y-zyNRleqqXoXb",[23500],{"_type":103,"marks":23501,"text":23502},[],"Therefore, there are some products, such as Birst or Qlik, that advertise themselves as a one-stop-shop for all things BI. These platforms might cover all the elements of a robust Business Intelligence strategy (also known as “Plug-and-Play”), from data warehousing to data modeling and visualization. In reality, these platforms are designed to be highly sticky within a business and attempting to develop outside of the platform can be rigid. This may be beneficial to a smaller firm since it helps them to streamline their data management and focus on growing their business. It might also work for a corporation with several data sources for different divisions, and the platform is utilized as a data aggregation tool for executive reporting.",[],{"_key":23505,"_type":99,"children":23506,"markDefs":23510,"style":799},"pAAGDSTM7iSwMK7xQk8xp",[23507],{"_type":103,"marks":23508,"text":23509},[],"To conclude, business intelligence is not just a collection of tools and dashboards. It is more of a platform but also a strategy. One that enables an organization to shift from reactive decision-making based on a descriptive tale to proactive decision-making based on data-driven analytics. Decisions that give the decision-maker confidence in the outcomes they are observing and seeking. This approach is unique to each company, and it must be determined not by creating criteria and comparing tools to what they can achieve, but by looking at the company as a whole and committing to a fundamental change in how business users interact with data.",[],{"_type":17,"current":23421},[23513,23514],{"_createdAt":12143,"_id":12144,"_rev":12145,"_type":8636,"_updatedAt":12146,"name":12147,"orderRank":12148,"uid":12149},{"_createdAt":19381,"_id":19382,"_rev":19383,"_type":8636,"_updatedAt":19384,"name":19385,"orderRank":10508,"uid":19386},{"_createdAt":23516,"_id":23517,"_rev":23518,"_system":23519,"_type":72,"_updatedAt":23522,"archived":126,"author":161,"category":23523,"date":23527,"description":23528,"image":161,"name":23537,"oldSlug":23538,"orderRank":23539,"reviewer":161,"sections":161,"seo":161,"slug":23540,"tags":23541},"2026-01-15T22:02:26Z","e2533463-6e93-4c9d-af5c-c0f9fbe71e0e","YkA36qTDOerM1fSJc31xlu",{"base":23520},{"id":23517,"rev":23521},"1XrksDlMkoAPinyrcvGhbq","2026-01-26T10:05:47Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":23524,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":23526,"uid":66},{"base":23525},{"id":57,"rev":61},{"_type":17,"current":66},"2023-03-03",[23529],{"_key":23530,"_type":99,"children":23531,"markDefs":23536,"style":107},"5e481db1700d",[23532],{"_key":23533,"_type":103,"marks":23534,"text":23535},"f74b6b03e1bf",[],"Anna Kostova has been part of Cosmos Thrace for more than a year and during that time she has proved to be valuable for the",[],"What do a business analysis career and making desserts have in common?","what-does-a-business-analysis-career-look-like-in-cosmos-thrace","0|1000ug:",{"_type":17,"current":23538},[23542],{"_createdAt":22463,"_id":22464,"_rev":22465,"_type":8636,"_updatedAt":22466,"name":22467,"orderRank":22468,"uid":22469},{"_createdAt":23544,"_id":23545,"_rev":23546,"_system":23547,"_type":72,"_updatedAt":23550,"archived":126,"author":161,"category":23551,"date":23555,"description":23556,"image":161,"name":23565,"oldSlug":23566,"orderRank":9645,"reviewer":161,"sections":23567,"seo":161,"slug":23685,"tags":23686},"2026-01-15T15:53:53Z","54786481-0570-4ba0-8c8b-c7674d5048be","7hw4Cb1llohacCi9MIIGPr",{"base":23548},{"id":23545,"rev":23549},"YkA36qTDOerM1fSJamXpNq","2026-01-28T09:32:07Z",{"_createdAt":32,"_id":33,"_rev":34,"_system":23552,"_type":12,"_updatedAt":38,"name":39,"orderRank":40,"slug":23554,"uid":42},{"base":23553},{"id":33,"rev":37},{"_type":17,"current":42},"2023-02-23",[23557],{"_key":23558,"_type":99,"children":23559,"markDefs":23564,"style":107},"350f0029a003",[23560],{"_key":23561,"_type":103,"marks":23562,"text":23563},"c4874b732079",[],"Nowadays cloud computing has become a necessity and it is no longer a question of whether businesses need it or not. Businesses should choose a",[],"Which IoT cloud solution should you choose and why?","which-iot-cloud-solution-to-choose-and-why",[23568],{"_createdAt":23569,"_id":23570,"_key":23571,"_ref":23570,"_rev":23549,"_type":168,"_updatedAt":23569,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":23572,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:38Z","4xIXiYwoCrKGNWLfN3_Li","0IIT-6C8S2z6nbPUV1wHl",[23573,23586,23593,23609,23616,23623,23630,23637,23644,23651,23658,23665],{"_key":23574,"_type":99,"children":23575,"markDefs":23585,"style":799},"uG7RaDhJQiR-aJ3pjLUtX",[23576,23579,23582],{"_type":103,"marks":23577,"text":23578},[],"Nowadays cloud computing has become a necessity and it is no longer a question of whether businesses need it or not. Businesses should choose a provider, however, there are various options on the market. The top three that stand out as top three cloud providers are ",{"_type":103,"marks":23580,"text":23581},[3055],"Azzure, AWS, and Google Cloud",{"_type":103,"marks":23583,"text":23584},[],". But even with that in mind the question “Which IoT cloud solution to choose” remains. In this article, we will go through the major factors of each hyper scaler so we can lessen your choice.",[],{"_key":23587,"_type":99,"children":23588,"markDefs":23592,"style":170},"GWrKY-qAVZSQvNwKCJ-6K",[23589],{"_type":103,"marks":23590,"text":23591},[],"Why cloud computing?",[],{"_key":23594,"_type":99,"children":23595,"markDefs":23606,"style":799},"iSFBoxWmwz1yvX1Jw_WMk",[23596,23599,23603],{"_type":103,"marks":23597,"text":23598},[],"But before that let’s answer the question “why cloud computing is so important”. In fact, there are countless reasons why it is vital for businesses, but we may say that the main reason is that it provides a great number of services in the public cloud. The global market value of the cloud computing industry is estimated to be $371 billion, and it is expected to reach $832 billion in 2025. (",{"_type":103,"marks":23600,"text":23602},[23601],"-I7bQS5WQfTyio_XFIGQh","researchandmarkets.com",{"_type":103,"marks":23604,"text":23605},[],") And the three main hyper scalers hold more than 80% of the global market share for cloud services for IoT.",[23607],{"_key":23601,"_type":173,"href":23608},"https://www.researchandmarkets.com/reports/5136796/cloud-computing-market-by-service-model?utm_source=GNOM&utm_medium=PressRelease&utm_code=8vg2fl&utm_campaign=1428189+-+Cloud+Computing+Industry+to+Grow+from+%24371.4+Billion+in+2020+to+%24832.1+Billion+by+2025%2c+at+a+CAGR+of+17.5%25&utm_exec=joca220prd",{"_key":23610,"_type":99,"children":23611,"markDefs":23615,"style":799},"dr034QKkEa2WUgRDbCXRw",[23612],{"_type":103,"marks":23613,"text":23614},[],"According to IoT Analytics, cloud services are classified into three main categories – application management, device management, and data management. Application management aims to help developers manage IoT applications as the name suggests. Device management service enables connected devices to work accurately by running updates and patches for the software and applications. Data management allows seamless connectivity, storing, and analyzing of IoT data.",[],{"_key":23617,"_type":99,"children":23618,"markDefs":23622,"style":170},"nssJwYeEhUhU0ZISGeWmv",[23619],{"_type":103,"marks":23620,"text":23621},[],"The top cloud service providers and their best qualities! Which IoT cloud solution to choose?",[],{"_key":23624,"_type":99,"children":23625,"markDefs":23629,"style":170},"8gfA_atzdj2MtvigIm7Ky",[23626],{"_type":103,"marks":23627,"text":23628},[],"AWS",[],{"_key":23631,"_type":99,"children":23632,"markDefs":23636,"style":799},"AnxTSetBR_vt8SQvJL4C9",[23633],{"_type":103,"marks":23634,"text":23635},[],"The first hyperscaler we will look at in detail is AWS, which is actually the first provider to introduce public cloud services in 2006 and expand it to IoT services later in 2015. As the first cloud provider, AWS remains innovative because of the earlier foundation that it builds on. As you can probably already tell, its biggest strength is public cloud services. Moreover, AWS is the leader in serverless computing because of its services Lambada and Athena. AWS is identified as the most enterprise-ready supplier due to its simplicity in delivering scalability, superior privacy measures, and security to its clients. The number of services that it offers is more than 200 in order to cater to any demand of its millions of users. In terms of IoT-focused services, AWS offers 13 and it has the largest portfolio. IoT Core is a service that ensures secure bi-directional communication for IoT devices; however, the client can decide whether to add a Device Management service to it. Last year, the provider added two new services (AWS IoT TwinMaker and FleetWise) and three other services that are relevant for IoT (RoboRunner, ExpressLink, and AWS Private 5G).",[],{"_key":23638,"_type":99,"children":23639,"markDefs":23643,"style":170},"Dcvh4o2NhYag9FXu0kNji",[23640],{"_type":103,"marks":23641,"text":23642},[],"Google Cloud",[],{"_key":23645,"_type":99,"children":23646,"markDefs":23650,"style":799},"fkgRzUdJ5-uS6hIBVp7Ty",[23647],{"_type":103,"marks":23648,"text":23649},[],"Google Cloud was released in 2008, two years after AWS, however, it managed to keep its position as one of the strongest challenges on the market. The greatest advantage of this cloud solution is its analytics capabilities. Although Google is the creator of the most-adopted cloud services, Google Cloud is a lot different from AWS and Azure. Its strongest sides are analytics, Big Data, AI, and ML. The most used cloud service is called Cloud IoT Core and it can be combined with other services by Google to come up with an end-to-end solution way easier. Clearly, Google is not focusing on IoT services for now, as they offer only one.",[],{"_key":23652,"_type":99,"children":23653,"markDefs":23657,"style":170},"dnNrUAqfwvTn60-HXzECu",[23654],{"_type":103,"marks":23655,"text":23656},[],"Microsoft Azure",[],{"_key":23659,"_type":99,"children":23660,"markDefs":23664,"style":799},"kA5_-rX94q5PpPY1cBMcY",[23661],{"_type":103,"marks":23662,"text":23663},[],"Last but not least, we will talk about Microsoft Azure. It has the strongest enterprise customer base of the three cloud solutions that we discussed in this article. The main reason why most clients prefer Azure over another cloud solution is that it is easy to add it to already existing Microsoft tools and usually companies are already using Microsoft products. That makes the transition to Azure easier than having to learn a completely new interface. Moreover, the company has IoT as a priority, like Google Cloud. Azure has nine IoT services in total, but the most used services are IoT Hub and Azure Edge. Azure allows data transferring without leaving its network, resulting in decreased costs, better security, and lower latency. In contrast to AWS Azure offers industry-specific services (Microsoft Cloud for Manufacturing). Another key differentiator is its ability to integrate with business intelligence tools like Power BI. The integration between Azure and Power B is very simple. On the other hand, integrating Power BI with AWS or Google Cloud might cause some problems. What is more, the UI is very user-friendly, even for people that do not have a programming background. And last, but not least while AWS features strong application management, Azure is more oriented toward device management.",[],{"_key":23666,"_type":99,"children":23667,"markDefs":23682,"style":799},"GrU864-F-6ehIn2fDDD4k",[23668,23671,23674,23677,23680],{"_type":103,"marks":23669,"text":23670},[],"We hope that this article has helped you understand a bit more about cloud computing and the top three providers. If you are still wondering which IoT cloud solution to choose, feel free to ",{"_type":103,"marks":23672,"text":789},[23673],"OElppC7UXYSishYZ0Wit9",{"_type":103,"marks":23675,"text":23676},[],". We will be more than happy to help! Also, check our other ",{"_type":103,"marks":23678,"text":19370},[23679],"wS9JUn50ndWLpyO4esEHx",{"_type":103,"marks":23681,"text":20704},[],[23683,23684],{"_key":23673,"_type":173,"href":19536},{"_key":23679,"_type":173,"href":19377},{"_type":17,"current":23566},[23687,23694,23700],{"_createdAt":23688,"_id":23689,"_rev":23690,"_type":8636,"_updatedAt":23691,"name":23692,"orderRank":4297,"uid":23693},"2026-01-20T12:23:30Z","e4cea08b-fdfd-4f07-88d9-0617ea1235b3","8sLbU849Ngr6bwLlc9Ufte","2026-01-20T12:23:32Z","Azure","azure",{"_createdAt":23695,"_id":23696,"_rev":23697,"_type":8636,"_updatedAt":23698,"name":23628,"orderRank":10811,"uid":23699},"2026-01-20T12:23:49Z","bfda4673-1e40-4e10-8698-85aee2232c7e","j3EW81XnW2YRbriXMJmhqK","2026-01-20T12:23:51Z","aws",{"_createdAt":23701,"_id":23702,"_rev":23703,"_type":8636,"_updatedAt":23704,"name":23705,"orderRank":52,"uid":23706},"2026-01-20T12:23:56Z","6f560614-d1aa-4e9f-aaf3-abd84894d0fa","j3EW81XnW2YRbriXMJmsM0","2026-01-20T12:23:58Z","GCP","gcp",{"_createdAt":23708,"_id":23709,"_rev":23710,"_system":23711,"_type":72,"_updatedAt":23714,"archived":126,"author":161,"category":23715,"date":23719,"description":23720,"image":161,"name":23729,"oldSlug":23730,"orderRank":23731,"reviewer":161,"sections":23732,"seo":161,"slug":23855,"tags":23856},"2026-01-15T22:02:56Z","0f74f5b2-b330-4785-a03f-323aee794166","2oGVswEwQBfyYUvi8REGCb",{"base":23712},{"id":23709,"rev":23713},"YkA36qTDOerM1fSJamfBch","2026-01-26T10:05:20Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":23716,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":23718,"uid":66},{"base":23717},{"id":57,"rev":61},{"_type":17,"current":66},"2023-02-16",[23721],{"_key":23722,"_type":99,"children":23723,"markDefs":23728,"style":107},"5f7f39270d4b",[23724],{"_key":23725,"_type":103,"marks":23726,"text":23727},"03967af401a6",[],"Svetoslav Ivanov has been part of Cosmos Thrace for almost two years. He joined the company as a student in a Dutch university where he",[],"What is the better place to develop your Python skills – A university in the Netherlands or a Bulgarian AI company?","the-better-place-to-develop-your-python-skills","0|1000uw:",[23733],{"_createdAt":23734,"_id":23735,"_key":23736,"_ref":23735,"_rev":23713,"_type":168,"_updatedAt":23734,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":23737,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:45:17Z","6ziIJrGpoChRTw4dxOjD1","0YqPBNqlR13LfTN9piLoR",[23738,23745,23752,23758,23765,23772,23779,23785,23792,23799,23806,23813,23820,23827,23834,23841],{"_key":23739,"_type":99,"children":23740,"markDefs":23744,"style":799},"R9bWona1NOMltUh4LbB5L",[23741],{"_type":103,"marks":23742,"text":23743},[],"Svetoslav Ivanov has been part of Cosmos Thrace for almost two years. He joined the company as a student in a Dutch university where he is studying Cognitive Science and Artificial Intelligence. He applied for the job of Python developer as he had already been taking Python courses but wanted to gain some real-life experience in the area and develop his Python skills. ",[],{"_key":23746,"_type":99,"children":23747,"markDefs":23751,"style":799},"9l6pYEQH_N-wDj7q7_U7l",[23748],{"_type":103,"marks":23749,"text":23750},[],"Two years later and on the verge of his university graduation, many colleagues would argue that he has become one of the best Python professionals in the company but also a great friend, colleague, and often the funniest guy in the room. ",[],{"_key":23753,"_type":99,"children":23754,"markDefs":23757,"style":170},"oWhm0vtJJpwk7Fcuwvfim",[23755],{"_type":103,"marks":23756,"text":22970},[],[],{"_key":23759,"_type":99,"children":23760,"markDefs":23764,"style":799},"FVIUua6JlvxQ-T-O66f3k",[23761],{"_type":103,"marks":23762,"text":23763},[],"The path to becoming part of Cosmos Thrace was pretty straightforward for Svetoslav. He was looking for a job to complement his studies when he found out that we were hiring. From the first interview, it was obvious that we shared common values and common goals. ",[],{"_key":23766,"_type":99,"children":23767,"markDefs":23771,"style":799},"3qwsPe4PdjEUbs9eirhx1",[23768],{"_type":103,"marks":23769,"text":23770},[],"Regarding the hiring process and the incentives behind applying for the job he says the following:",[],{"_key":23773,"_type":99,"children":23774,"markDefs":23778,"style":799},"rGTDLGVwzdEBsTITbIqPC",[23775],{"_type":103,"marks":23776,"text":23777},[],"“I was very passionate about Python programming in particular, which was one of the main languages used in Data Science and AI, hence in my university program, so I was very familiar with it. I found out that there was an open Python Developer position here at Cosmos Thrace, so I just wanted to try it out and get real-life programming experience. Looking at it now, I think that it was a great decision.“",[],{"_key":23780,"_type":99,"children":23781,"markDefs":23784,"style":170},"ZoJu35P7KvY0W9ZMuo5bv",[23782],{"_type":103,"marks":23783,"text":23012},[],[],{"_key":23786,"_type":99,"children":23787,"markDefs":23791,"style":799},"b3AfqNlh71kqEMMc6916N",[23788],{"_type":103,"marks":23789,"text":23790},[],"“Being part of the company for almost two years now, I can say that everyone in it is open to a lot of changes and suggestions. Both on a project basis and on a company basis, you can propose a lot of things and your opinion is always heard. Another big benefit is that you have access to people who are higher up in management and are always open to assisting you with any issues that you might have.” ",[],{"_key":23793,"_type":99,"children":23794,"markDefs":23798,"style":799},"fOPwOJCGjirVcdM0zqDXe",[23795],{"_type":103,"marks":23796,"text":23797},[],"On top of that Svetoslav mentions that the environment within the company is very friendly, but at times can be competitive, leading to minor project disagreements. However, he took this as a learning experience, stating that it helped him improve his managerial and soft skills.",[],{"_key":23800,"_type":99,"children":23801,"markDefs":23805,"style":170},"CQmfTrjtD3PtORZ4ifk0A",[23802],{"_type":103,"marks":23803,"text":23804},[],"Professional and personal development in the past two years",[],{"_key":23807,"_type":99,"children":23808,"markDefs":23812,"style":799},"IMgm5GQFIwRGmP4ozLb80",[23809],{"_type":103,"marks":23810,"text":23811},[],"“Honestly, I develop my Python skills way more at Cosmos Thrace than at university. I got involved in projects that demand really advanced knowledge and that made me grow a lot in terms of Python development. The projects were harder than what I have been used to but also the colleagues were more knowledgeable and were always open to helping me , while leaving the space for me to be more independent.",[],{"_key":23814,"_type":99,"children":23815,"markDefs":23819,"style":799},"coHQXvaVQDTggxAjvRxRw",[23816],{"_type":103,"marks":23817,"text":23818},[],"“However, in the future I see myself developing more on the management side rather than on the software engineering one. I had the opportunity to do it a few times in the past year and I really enjoy it. I feel like I am good at delegating tasks and also having an overall view of the state of the project and what needs to be done for it to smoothly move forward.” ",[],{"_key":23821,"_type":99,"children":23822,"markDefs":23826,"style":170},"CGsw1Vepuy8TMPRhZJqax",[23823],{"_type":103,"marks":23824,"text":23825},[],"Life outside Cosmos Thrace",[],{"_key":23828,"_type":99,"children":23829,"markDefs":23833,"style":799},"Jnev4wX_iEFSfa76__kta",[23830],{"_type":103,"marks":23831,"text":23832},[],"Being both enrolled in university and working professionally has its downsides as well. As Svetoslav mentions, currently he does not have enough time to practice his favorite hobbies. He is generally a very active person as most of his hobbies are in the sporting sphere. Before having such a busy schedule he was often in the gym doing some weightlifting training or at the boxing gym, sparring. ",[],{"_key":23835,"_type":99,"children":23836,"markDefs":23840,"style":799},"1rzl8u7CsnMQBkorkAmBV",[23837],{"_type":103,"marks":23838,"text":23839},[],"“Also I used to love running – I have actually completed the Sofia marathon three times. So I have a lot of kilometers behind me. Actually, programming is a lot like running a marathon – it takes a lot of time and effort but you are always satisfied with the end result. I can also mention gaming as something I like – I would say that most of the people my age fell in love with programming because of computer games.” ",[],{"_key":23842,"_type":99,"children":23843,"markDefs":23853,"style":799},"QbqteDsiTTv2rogW850g9",[23844,23847,23850],{"_type":103,"marks":23845,"text":23846},[],"Take a look at our ",{"_type":103,"marks":23848,"text":20175},[23849],"lBnfSxmM92iIH6mMA7-E9",{"_type":103,"marks":23851,"text":23852},[]," page in order to be able to develop your Python skills as well!",[23854],{"_key":23849,"_type":173,"href":20182},{"_type":17,"current":23730},[23857,23858],{"_createdAt":23096,"_id":23097,"_rev":23098,"_type":8636,"_updatedAt":23099,"name":23100,"orderRank":23101,"uid":23102},{"_createdAt":22463,"_id":22464,"_rev":22465,"_type":8636,"_updatedAt":22466,"name":22467,"orderRank":22468,"uid":22469},{"_createdAt":23860,"_id":23861,"_rev":23862,"_system":23863,"_type":72,"_updatedAt":23866,"archived":126,"author":161,"category":23867,"date":23871,"description":23872,"image":161,"name":23881,"oldSlug":23882,"orderRank":23883,"reviewer":161,"sections":23884,"seo":161,"slug":24007,"tags":24008},"2026-01-15T22:03:27Z","713868d0-8fa0-4105-8686-fa88379d6c1d","Vn4VZyigw0pktYT2rhU7jk",{"base":23864},{"id":23861,"rev":23865},"ZfaOePOqVJD5r4KHzTWyVG","2026-01-26T10:04:28Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":23868,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":23870,"uid":66},{"base":23869},{"id":57,"rev":61},{"_type":17,"current":66},"2023-01-31",[23873],{"_key":23874,"_type":99,"children":23875,"markDefs":23880,"style":107},"e3f700dba8c3",[23876],{"_key":23877,"_type":103,"marks":23878,"text":23879},"cd61e233bbc7",[],"Darinka Velikova is one of our senior software developers and has been part of the company for more than six months. 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She is mainly focused in the field of data warehousing and is now one of our most knowledgeable team members in it. Prior to joining Cosmos Thrace, she worked for 12 years in one of the biggest European telecommunication companies. So, she went from a big company to a startup but does it worth it?",[],{"_key":23898,"_type":99,"children":23899,"markDefs":23903,"style":799},"HIenju-mXSk4rD827Jphk",[23900],{"_type":103,"marks":23901,"text":23902},[],"If we had asked her a year ago whether she would change her previous job and join a startup, her answer would have definitely been “No”. However, let’s find out what made her trade off 12 years in a well-established international company for a startup that is now making a big statement to the world!",[],{"_key":23905,"_type":99,"children":23906,"markDefs":23909,"style":170},"hedxuGjasgbwG6zKzvL7V",[23907],{"_type":103,"marks":23908,"text":22970},[],[],{"_key":23911,"_type":99,"children":23912,"markDefs":23916,"style":799},"z1cuaaw0-9qd3TMUq3JbG",[23913],{"_type":103,"marks":23914,"text":23915},[],"“Viktor Elevterov (our CEO) and I knew each other because in the past we have worked together on some projects. So, he gave me a call and offered me the opportunity to join Cosmos Thrace. At that point, I had already worked in my former company for more than ten years and the offer to join a startup was at the same time interesting but also very different from what I was used to.”",[],{"_key":23918,"_type":99,"children":23919,"markDefs":23923,"style":799},"JdfPSijI1UywbIQSx8oLL",[23920],{"_type":103,"marks":23921,"text":23922},[],"She says that at that exact moment she was not particularly looking for a new job. However, Viktor being so persistent convinced Darinka and she saw an opportunity to develop her professional career based on the innovative and interesting projects the company works on. ",[],{"_key":23925,"_type":99,"children":23926,"markDefs":23929,"style":170},"ggEDRMDLSnDmmFkuV_p4a",[23927],{"_type":103,"marks":23928,"text":23012},[],[],{"_key":23931,"_type":99,"children":23932,"markDefs":23936,"style":799},"lfUgg59Dmd_o6-1kEzE6y",[23933],{"_type":103,"marks":23934,"text":23935},[],"“I have been in the company for around six months now. What I like the most so far is the team and people I work with. I like the fact that we help each other constantly and whenever you have a problem or question everyone is open to assisting you or giving you an answer.” ",[],{"_key":23938,"_type":99,"children":23939,"markDefs":23943,"style":799},"fF7OlMBjvBT7YwO5c_xjl",[23940],{"_type":103,"marks":23941,"text":23942},[],"For Darinka, being able to choose where to work from is a very important factor as well. What she enjoys a lot is the freedom that each team member has in choosing his or her workplace. ",[],{"_key":23945,"_type":99,"children":23946,"markDefs":23950,"style":799},"rXfBMKkw4_nq_ap7N4g78",[23947],{"_type":103,"marks":23948,"text":23949},[]," “In my opinion we should all have the right to choose where we work from. At Cosmos Thrace we have both an office where we can go whenever we want and we can also work from home. ",[],{"_key":23952,"_type":99,"children":23953,"markDefs":23957,"style":799},"J3zeNRwostoIGAhf0bp8o",[23954],{"_type":103,"marks":23955,"text":23956},[],"Darinka feels she is in the right place in Cosmos Thrace because there are constantly new and interesting things happening. ",[],{"_key":23959,"_type":99,"children":23960,"markDefs":23964,"style":799},"YYvNdonBmJqCEambYKA8x",[23961],{"_type":103,"marks":23962,"text":23963},[],"“For example, in our team there are many juniors and when I joined, the project we worked on was starting to lean away from the proper data warehouse structure. So, I had to assist them to put everything in place. This was very interesting for me and I really enjoy such challenges.”",[],{"_key":23966,"_type":99,"children":23967,"markDefs":23970,"style":170},"oy0ZScUy_4kJVAGQUgq5h",[23968],{"_type":103,"marks":23969,"text":23825},[],[],{"_key":23972,"_type":99,"children":23973,"markDefs":23977,"style":799},"e32nQXcNdmcAMjh8XkcaQ",[23974],{"_type":103,"marks":23975,"text":23976},[],"Besides being a well-established professional in her field, Darinka greatly enjoys her free time. Her main passion is folk dancing, which she has been doing for many years, and until recently, was even performing on stage.",[],{"_key":23979,"_type":99,"children":23980,"markDefs":23984,"style":799},"GIjyILkoeUXEL4-QmGak0",[23981],{"_type":103,"marks":23982,"text":23983},[],"“At the moment, I am practicing just for the joy of it. It makes me forget all the worries in life and while I am dancing, I’m always smiling. It is a feeling you cannot describe but is definitely something that relaxes my mind and re-charges my batteries.“",[],{"_key":23986,"_type":99,"children":23987,"markDefs":24004,"style":799},"EpOf2j-A7miqy5ue5ROLS",[23988,23991,23995,23998,24002],{"_type":103,"marks":23989,"text":23990},[],"Are you also considering transitioning from a big company to a startup? 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At the same time data quantity and quality grow at breakneck speeds.",[],"What are the top 5 most lucrative use cases of AI until 2025?","what-are-the-top-5-most-lucrative-use-cases-of-ai-until-2025","0|1000eg:",[24124],{"_createdAt":24125,"_id":24126,"_key":24127,"_ref":24126,"_rev":24128,"_type":168,"_updatedAt":24125,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":24129,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:39Z","QfskXELeDWCopIMQ-2Ya-","xUTpsUhaDn9mH4IdEgWuZ","ZfaOePOqVJD5r4KHzTTIf6",[24130,24136,24143,24150,24157,24164,24171,24178,24185,24192,24199,24206,24213,24220,24227,24234,24241,24248,24255,24262,24269,24276,24283,24297,24304,24311,24318,24325,24332,24339,24345,24352],{"_key":24131,"_type":99,"children":24132,"markDefs":24135,"style":799},"cj8e5MKgq0ej7l3FP6gag",[24133],{"_type":103,"marks":24134,"text":24118},[],[],{"_key":24137,"_type":99,"children":24138,"markDefs":24142,"style":799},"jMPfxKsrslZ9KA2ZbR2xa",[24139],{"_type":103,"marks":24140,"text":24141},[],"What does this mean for the future of your business? ",[],{"_key":24144,"_type":99,"children":24145,"markDefs":24149,"style":799},"ICingVn8xaCTylhrPmiR3",[24146],{"_type":103,"marks":24147,"text":24148},[],"We recently got a peak at the forecast for global revenues of different fields of AI (see below).",[],{"_key":24151,"_type":99,"children":24152,"markDefs":24156,"style":799},"EIxbdr2Q4WSNMkMR9nAjQ",[24153],{"_type":103,"marks":24154,"text":24155},[],"Naturally, this got us thinking: ‘’Why these areas?’’, so we combed through a lot of research, both our own and externally sourced. ",[],{"_key":24158,"_type":99,"children":24159,"markDefs":24163,"style":799},"okiJLUd7oGvVginm4y1yk",[24160],{"_type":103,"marks":24161,"text":24162},[],"So, here are our findings on the top 5 most lucrative use cases of AI until 2025.",[],{"_key":24165,"_type":99,"children":24166,"markDefs":24170,"style":170},"Wdgg0uG3mzwHDax_AYx_3",[24167],{"_type":103,"marks":24168,"text":24169},[],"1.Static image recognition, classification, and tagging",[],{"_key":24172,"_type":99,"children":24173,"markDefs":24177,"style":799},"-9LjFNoQbJUb3LLXqfvmd",[24174],{"_type":103,"marks":24175,"text":24176},[],"A computer ‘‘vision’’ technique that allows for the interpretation and categorization of what is “seen” in images or videos. Often referred to as “image classification” or “image labelling” (or tagging), this task is essential in solving many computers vision-based ML issues.",[],{"_key":24179,"_type":99,"children":24180,"markDefs":24184,"style":799},"o7LsAnCdg_p3gWqfBuLBP",[24181],{"_type":103,"marks":24182,"text":24183},[],"Some interesting current and potential uses: ",[],{"_key":24186,"_type":99,"children":24187,"level":230,"listItem":231,"markDefs":24191,"style":107},"wDmyzr4Azte1fJb5rXBth",[24188],{"_type":103,"marks":24189,"text":24190},[],"Customer analysis – learning more about individuals through detection of logos or text in the products they consume and use.",[],{"_key":24193,"_type":99,"children":24194,"level":230,"listItem":231,"markDefs":24198,"style":107},"hUz1tOof5qOq10zFMmm1U",[24195],{"_type":103,"marks":24196,"text":24197},[],"Facial verification of users – Face ID",[],{"_key":24200,"_type":99,"children":24201,"level":230,"listItem":231,"markDefs":24205,"style":107},"PDULFOUn5ivTCwh2EOg5R",[24202],{"_type":103,"marks":24203,"text":24204},[],"Tagging of images – using tags or keywords on images to organize and sift through them better. Enables organization and categorization.",[],{"_key":24207,"_type":99,"children":24208,"level":230,"listItem":231,"markDefs":24212,"style":107},"hjdtKA_LzLt0Y5ntivH91",[24209],{"_type":103,"marks":24210,"text":24211},[],"Content moderation for different purposes related to social media",[],{"_key":24214,"_type":99,"children":24215,"level":230,"listItem":231,"markDefs":24219,"style":107},"6EsyhW4JSBDHK7JjpGgPA",[24216],{"_type":103,"marks":24217,"text":24218},[],"Accessibility – for the visually impaired. ",[],{"_key":24221,"_type":99,"children":24222,"level":230,"listItem":231,"markDefs":24226,"style":107},"uEfvo634MJN3LcSJph82b",[24223],{"_type":103,"marks":24224,"text":24225},[],"Visual Search – using real images to procure more reliable online searches. Allows for better targeting based on shopper behaviours and interests. ",[],{"_key":24228,"_type":99,"children":24229,"markDefs":24233,"style":170},"wDZlCN74I9hvh-LFQ-lgC",[24230],{"_type":103,"marks":24231,"text":24232},[],"2. Algorithmic trading strategy performance improvement",[],{"_key":24235,"_type":99,"children":24236,"markDefs":24240,"style":799},"i0VzW5-jZfJJ8THsA0wD-",[24237],{"_type":103,"marks":24238,"text":24239},[],"This uses AI to place, buy and sell orders automatically according to a specified set of rules or logic. These rules are collectively referred to as the trading algorithm. ",[],{"_key":24242,"_type":99,"children":24243,"markDefs":24247,"style":799},"8pKUiVHe7arao2czJ8kqm",[24244],{"_type":103,"marks":24245,"text":24246},[],"So, why is it lucrative?",[],{"_key":24249,"_type":99,"children":24250,"markDefs":24254,"style":799},"Zoiay5WAvrYvGjLV06fmW",[24251],{"_type":103,"marks":24252,"text":24253},[],"With stock, bond, Forex, Crypto, and all other forms of trading currently using AI algorithm trading, optimization and improvement in this field can only bring higher and higher returns. From reduced transaction costs to precise execution of trades, and accurate formulation of decisions while accounting for multiple factors. ",[],{"_key":24256,"_type":99,"children":24257,"markDefs":24261,"style":170},"xMOBIBNshz68-sVAmQu9b",[24258],{"_type":103,"marks":24259,"text":24260},[],"3. Efficient, Scalable processing of patient data",[],{"_key":24263,"_type":99,"children":24264,"markDefs":24268,"style":799},"S__yynqdoNxrKq5mmj4zm",[24265],{"_type":103,"marks":24266,"text":24267},[],"AI and ML are used in the medical field to search through medical data and find insights to help improve health outcomes and patient experiences. This also helps medical practitioners by saving valuable time otherwise spent in searching through data. Clinical decision support provided by AI is still improving. CT scans, x-rays, MRI’s, and other graphical data is also analysed with great success. ",[],{"_key":24270,"_type":99,"children":24271,"markDefs":24275,"style":799},"G06RwrOwwJj6iU2vTCe8z",[24272],{"_type":103,"marks":24273,"text":24274},[],"Disease detection and diagnosis is also something that AI can provide. The current pandemic boosted the development of AI in healthcare, and this growth is predicted to increase greatly by 2025, with accelerated drug development being a massive part of the predicted revenue. AI can formulate better drug designs and find new drug combinations easier. ",[],{"_key":24277,"_type":99,"children":24278,"markDefs":24282,"style":170},"4aCiLM8ew3-osAObJmTxi",[24279],{"_type":103,"marks":24280,"text":24281},[],"4. Predictive Maintenance",[],{"_key":24284,"_type":99,"children":24285,"markDefs":24295,"style":799},"zgwAHw2_ny6KICdKjynBn",[24286,24289,24292],{"_type":103,"marks":24287,"text":24288},[],"When it comes to why ",{"_type":103,"marks":24290,"text":22811},[24291],"f1X76Fn5QxH-vDj2eGmrB",{"_type":103,"marks":24293,"text":24294},[]," is expected to grow so much, there is one main prediction in development – cognitive maintenance.",[24296],{"_key":24291,"_type":173,"href":22826},{"_key":24298,"_type":99,"children":24299,"markDefs":24303,"style":799},"F_axV1RXhTqhuNAEaE57u",[24300],{"_type":103,"marks":24301,"text":24302},[],"Cognitive maintenance – based on cognitive analytics where AI can learn from past actions and results, can look for correlations and prescribe courses of action. It changes a company’s behaviour from reactive to prescriptive. In short, data from connected equipment and products is analysed, combined with service knowledge and data, and using the result to improve equipment and uptime.",[],{"_key":24305,"_type":99,"children":24306,"markDefs":24310,"style":799},"ukNj_TBtXmDim7hcCVXMR",[24307],{"_type":103,"marks":24308,"text":24309},[],"So, while Predictive maintenance accurately identifies and predicts faults in equipment, cognitive maintenance then provides the engineers responsible with detailed information on how to prevent or repair the equipment.",[],{"_key":24312,"_type":99,"children":24313,"markDefs":24317,"style":170},"esxutS_cKyDQLTovKEXbh",[24314],{"_type":103,"marks":24315,"text":24316},[],"5. Object identification, detection, classification, tracking",[],{"_key":24319,"_type":99,"children":24320,"markDefs":24324,"style":799},"qedJQ1hqwXKWWjoCZCb_b",[24321],{"_type":103,"marks":24322,"text":24323},[],"Object detection, similar to the first point of our article, is used to analyse pictures and video frames. The difference however is that in the case of object detection, the AI analyses the image or video frame looking for a specific visual object. The goal is to answer the question ‘’What objects are where?’’. ",[],{"_key":24326,"_type":99,"children":24327,"markDefs":24331,"style":799},"wWwIQNU8CDD9nu_3FY7-4",[24328],{"_type":103,"marks":24329,"text":24330},[],"How will this field earn the predicted revenue? ",[],{"_key":24333,"_type":99,"children":24334,"markDefs":24338,"style":799},"-fc7Y4enosWVJRcJhLUa5",[24335],{"_type":103,"marks":24336,"text":24337},[],"There are many applications, such as healthcare monitoring, autonomous driving, video surveillance, anomaly detection, or robot vision. Agriculture has also recently started to benefit from this technology with animal detection – counting and monitoring. The broad and varied uses for this tool are what makes it lucrative.",[],{"_key":24340,"_type":99,"children":24341,"markDefs":24344,"style":170},"uUawMyZWnyPoGKwbnlne0",[24342],{"_type":103,"marks":24343,"text":4733},[],[],{"_key":24346,"_type":99,"children":24347,"markDefs":24351,"style":799},"pAsueBJiPpAVJf1ZpdJNC",[24348],{"_type":103,"marks":24349,"text":24350},[],"We believe that the list is surprisingly on track with which areas of AI will top the charts, however, there is an argument that the top 5 most lucrative use cases of AI are interchangeable, and only time can show which developments prove to be ahead of others. In any case AI will keep developing at breakneck speeds and drive our possibilities forward. ",[],{"_key":24353,"_type":99,"children":24354,"markDefs":24367,"style":799},"YLp078Tq6dpUd7ElSr3H2",[24355,24358,24361,24364],{"_type":103,"marks":24356,"text":7898},[24357],"RyiA-mm83zmJIEA104qRt",{"_type":103,"marks":24359,"text":24360},[]," believes that implementing AI in your business can future proof it, as having the foundations set now, can lead to much easier adoption of future technologies. ",{"_type":103,"marks":24362,"text":18707},[24363],"5MklZpbzkg15jdGa16Po7",{"_type":103,"marks":24365,"text":24366},[]," if you would like to discuss the ‘’why?’’ and ‘’how’’ of the most lucrative aspects of AI development.",[24368,24369],{"_key":24357,"_type":173,"href":19536},{"_key":24363,"_type":173,"href":24370},"https://calendly.com/viktor-todorov/free-introductory-call?month=2023-05",{"_type":17,"current":24121},[24373,24374,24381],{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":24375,"_id":24376,"_rev":24377,"_type":8636,"_updatedAt":24378,"name":24379,"orderRank":13966,"uid":24380},"2026-01-20T12:26:14Z","cdb96480-3fba-4aea-b61a-2ed1bc6553a1","8sLbU849Ngr6bwLlc9YVO2","2026-01-20T12:26:22Z","Logistics","logistics",{"_createdAt":20710,"_id":20711,"_rev":20712,"_type":8636,"_updatedAt":20713,"name":20714,"orderRank":15218,"uid":20715},{"_createdAt":24383,"_id":24384,"_rev":24385,"_system":24386,"_type":72,"_updatedAt":24389,"archived":126,"author":161,"category":24390,"date":24394,"description":24395,"image":161,"name":24404,"oldSlug":24405,"orderRank":24406,"reviewer":161,"sections":24407,"seo":161,"slug":24526,"tags":24527},"2026-01-15T15:55:38Z","00955b18-4875-43a0-9634-9ffffd70f189","3x1HJiv3wwU7cYVoHtTdS2",{"base":24387},{"id":24384,"rev":24388},"YkA36qTDOerM1fSJamXs0i","2026-01-28T08:51:32Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":24391,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":24393,"uid":30},{"base":24392},{"id":21,"rev":25},{"_type":17,"current":30},"2022-12-16",[24396],{"_key":24397,"_type":99,"children":24398,"markDefs":24403,"style":107},"c86c1cf0e0de",[24399],{"_key":24400,"_type":103,"marks":24401,"text":24402},"9a235b688a8f",[],"AI-driven solutions are businesses’ key preferences when it comes to optimization. Or is it? Despite today’s businesses’ increasing expenditures on artificial intelligence (AI), the C-suite’s",[],"How to increase executive confidence in AI-assisted decisions","how-to-increase-executive-confidence-in-ai-assisted-decisions","0|1000fc:",[24408],{"_createdAt":24409,"_id":24410,"_key":24411,"_ref":24410,"_rev":24388,"_type":168,"_updatedAt":24409,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":24412,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:43Z","6goOZebC6xuPZiLwCSZMy","RkbyMtHOWylGK82EUnsbt",[24413,24420,24427,24434,24441,24448,24455,24462,24469,24476,24483,24490,24497,24504,24511],{"_key":24414,"_type":99,"children":24415,"markDefs":24419,"style":170},"_9LUm6OaMRbr9AaXEBcbY",[24416],{"_type":103,"marks":24417,"text":24418},[],"AI-driven solutions are businesses’ key preferences when it comes to optimization. Or is it?",[],{"_key":24421,"_type":99,"children":24422,"markDefs":24426,"style":799},"YcXG1S2jXMjvfT22sQTLJ",[24423],{"_type":103,"marks":24424,"text":24425},[],"Despite today’s businesses’ increasing expenditures on artificial intelligence (AI), the C-suite’s belief in AI may be hit or miss. Is it just that CEOs are wary of a new and unproven technology, or is there anything more to it? Executives have traditionally opposed the use of data analytics for higher-level decision-making, preferring instead to depend on gut-level choices based on field experience rather than AI-assisted suggestions. So, how to increase executive confidence in AI?",[],{"_key":24428,"_type":99,"children":24429,"markDefs":24433,"style":799},"J8aXXL2bhe12R6VT-ZMNZ",[24430],{"_type":103,"marks":24431,"text":24432},[],"In several sectors, AI has been widely embraced for tactical, lower-level decision-making – credit scoring, upselling suggestions, chatbots, and machine performance management are just a few examples. However, it has yet to demonstrate its worth when it comes to higher-level strategic decisions like recasting product lines, altering corporate strategy, reallocating human resources across departments, or forming new partnerships.",[],{"_key":24435,"_type":99,"children":24436,"markDefs":24440,"style":170},"1ixXFl5p8-HiR8NPwRcQc",[24437],{"_type":103,"marks":24438,"text":24439},[],"The first step in increasing executive confidence in AI is by creating reliable models that provide businesses with consistent insights.",[],{"_key":24442,"_type":99,"children":24443,"markDefs":24447,"style":799},"J5QLew9Fdnhjx76oavXNR",[24444],{"_type":103,"marks":24445,"text":24446},[],"Executive apprehension can originate from bad experiences, such as when an AI system produces false sales results. A lack of data quality is a common factor in almost every unsuccessful AI effort. Structured data was prevalent in the traditional business model, which categorized data as it entered from the source and made it very straightforward to put it to immediate use. However, AI also consumes large volumes of unstructured data in creating ML and DL models.",[],{"_key":24449,"_type":99,"children":24450,"markDefs":24454,"style":799},"3r39BE2Rkx9gTUYOzLEIZ",[24451],{"_type":103,"marks":24452,"text":24453},[],"Therefore, it is no surprise that many data scientists devote half of their time to data preparation, which is still the most important task in developing dependable AI models that produce accurate results. Context and dependability are essential for gaining executive confidence. There are various AI tools available to aid with data prep – from synthetic data to data debiasing and data purification.",[],{"_key":24456,"_type":99,"children":24457,"markDefs":24461,"style":170},"D2EecYYgXvAWeW4sbgqFY",[24458],{"_type":103,"marks":24459,"text":24460},[],"Secondly, after the whole data preparation, there should also be an avoidance of data biases to boost confidence in executives.",[],{"_key":24463,"_type":99,"children":24464,"markDefs":24468,"style":799},"ek6Ndpp6gTpoWdm_oqdLK",[24465],{"_type":103,"marks":24466,"text":24467},[],"Executive apprehension may stem from a well-founded fear that AI outcomes would lead to discrimination inside their businesses or harm customers. In the same way, AI bias might be swaying company choices in the wrong direction. When an AI model is trained on skewed data, the model will be skewed and provide skewed recommendations.",[],{"_key":24470,"_type":99,"children":24471,"markDefs":24475,"style":799},"K-W7BeZiQRgGouVlk-jiM",[24472],{"_type":103,"marks":24473,"text":24474},[],"Hence, data utilized in higher-level decision-making should be extensively examined to ensure that executives have confidence that information is proven, authoritative, validated, and derived from trustworthy sources. It must be free of known discriminatory practices that can cause algorithms to be skewed. For example, discrimination may be considerably decreased at a low incremental cost by regulating categorization accuracy. Controlling discriminating, reducing dataset distortion, and retaining usefulness should be the focus of this data pre-processing optimization.",[],{"_key":24477,"_type":99,"children":24478,"markDefs":24482,"style":170},"sFRu_U6WCXp979g25tqSJ",[24479],{"_type":103,"marks":24480,"text":24481},[],"And here we reach the question of AI ethics in decision-making processes.",[],{"_key":24484,"_type":99,"children":24485,"markDefs":24489,"style":799},"DYmqzrq4Zt_Lj4sh12wrA",[24486],{"_type":103,"marks":24487,"text":24488},[],"Executive reluctance may reflect the reality that businesses are under great pressure to guarantee moral and ethical operations. Currently, research institutions try to apply human values to AI, by converting them into engineering terminology that robots can grasp. For instance, Stuart Russell, a computer science professor at the University of California, Berkeley, pioneered the Value Alignment Principle, which basically “rewards” AI systems for more acceptable conduct. AI systems or robots may be taught to read tales, understand appropriate sequences of events, and better reflect successful behavior.",[],{"_key":24491,"_type":99,"children":24492,"markDefs":24496,"style":170},"suCumNMN9HH3TnAruVLaV",[24493],{"_type":103,"marks":24494,"text":24495},[],"Lastly, we should consider transparency when implementing and relying on AI solutions.",[],{"_key":24498,"_type":99,"children":24499,"markDefs":24503,"style":799},"BX2TX-S9BaRLv9JTVk2Mu",[24500],{"_type":103,"marks":24501,"text":24502},[],"If there is a lack of transparency, executives may be hesitant to absorb AI judgments. Thus, the data used to train algorithms must be stored securely, validated, audited, and encrypted to be held accountable. Immutable and auditable storage is also possible with emerging approaches like blockchain and other distributed ledger technologies. Furthermore, a third-party governance system should verify that AI choices are not just understandable but also founded on factual data. Ultimately, it should be feasible to demonstrate that a human, given the identical data, would come to the same conclusions.",[],{"_key":24505,"_type":99,"children":24506,"markDefs":24510,"style":799},"IXQVwfCB1GsXNxyS4vqE0",[24507],{"_type":103,"marks":24508,"text":24509},[],"For strategic reasons, more AI-assisted decision-making will inevitably be observed in the executive suite. Furthermore, AI can aid people in decision-making to conduct enhanced intelligence, rather than deliver perfect insights. Assuring that the output of these AI-assisted judgments is based on trustworthy, impartial, explainable, ethical, and transparent insights will help business leaders have confidence in AI-assisted decisions not only today but also in the future.",[],{"_key":24512,"_type":99,"children":24513,"markDefs":24524,"style":799},"UgPPdDba8XdSsPReYbVOE",[24514,24517,24521],{"_type":103,"marks":24515,"text":24516},[],"Did we answer the question “How to increase executive confidence in AI”? If yes, ",{"_type":103,"marks":24518,"text":24520},[24519],"3cL-6ODniqyWIa_wONe_9","book a free call ",{"_type":103,"marks":24522,"text":24523},[],"with us and let us help you in you digital transformation journey! ",[24525],{"_key":24519,"_type":173,"href":19536},{"_type":17,"current":24405},[24528,24529,24530],{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":11543,"_id":11544,"_rev":11545,"_type":8636,"_updatedAt":11546,"name":11547,"orderRank":11548,"uid":11549},{"_createdAt":13100,"_id":13101,"_rev":13102,"_type":8636,"_updatedAt":13103,"name":13104,"orderRank":12215,"uid":13105},{"_createdAt":24532,"_id":24533,"_rev":24534,"_system":24535,"_type":72,"_updatedAt":24538,"archived":126,"author":161,"category":24539,"date":24394,"description":24543,"image":161,"name":24552,"oldSlug":24553,"orderRank":24554,"reviewer":161,"sections":24555,"seo":161,"slug":24680,"tags":24681},"2026-01-15T15:56:05Z","5f210086-0bfa-4e1f-b226-33713fc52c60","ir9xdmjsDvNqVMLz9XlfjF",{"base":24536},{"id":24533,"rev":24537},"ZfaOePOqVJD5r4KHzTTKks","2026-01-28T08:26:16Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":24540,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":24542,"uid":30},{"base":24541},{"id":21,"rev":25},{"_type":17,"current":30},[24544],{"_key":24545,"_type":99,"children":24546,"markDefs":24551,"style":107},"a0538221b461",[24547],{"_key":24548,"_type":103,"marks":24549,"text":24550},"220160568ecf",[],"Now that the AI buzz has worn off, the technology’s major problems are focused on making profits rather than finding out how to make it",[],"How to Get Returns from AI Investments?","how-to-get-returns-from-ai-investments","0|1000fs:",[24556],{"_createdAt":24557,"_id":24558,"_key":24559,"_ref":24558,"_rev":24537,"_type":168,"_updatedAt":24557,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":24560,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:45Z","Pj4EYGAS6CBq7t_81uIzM","cW7tiho7Vlsi98rgy3HFj",[24561,24568,24575,24582,24589,24596,24603,24610,24617,24624,24631,24638,24645,24652,24659],{"_key":24562,"_type":99,"children":24563,"markDefs":24567,"style":799},"EPIpG8mjp9b0iGpKowfrb",[24564],{"_type":103,"marks":24565,"text":24566},[],"Now that the AI buzz has worn off, the technology’s major problems are focused on making profits rather than finding out how to make it helpful. AI can offer great value for many enterprises, thanks to the expanding number of AI professionals and machine learning services. When it comes to AI, however, corporations frequently fail to recoup their initial expenditures. Moreover, the first question they ask before starting the implementation is “How to get returns from AI investments?”",[],{"_key":24569,"_type":99,"children":24570,"markDefs":24574,"style":799},"uYj_r0I66cBC4rmezuTqa",[24571],{"_type":103,"marks":24572,"text":24573},[],"The foundation of the problem is that it is impossible to earn economic returns on technology that has not yet been put into production. Furthermore, even when AI programs are launched, they frequently fail to deliver the desired results.",[],{"_key":24576,"_type":99,"children":24577,"markDefs":24581,"style":170},"0aXiakXnKUFScal_PUIc0",[24578],{"_type":103,"marks":24579,"text":24580},[],"However, companies who want to get higher returns on AI investments should first consider that AI is data-driven",[],{"_key":24583,"_type":99,"children":24584,"markDefs":24588,"style":799},"flIjNl1TlZkpHUN4bG0gQ",[24585],{"_type":103,"marks":24586,"text":24587},[],"Surprisingly, a lack of data culture is one of the most common issues that businesses encounter when it comes to reaching AI’s full potential. AI attempts will almost certainly fail if the company’s management and senior workers lack data competence. Even the most carefully developed AI systems will fall short of their full potential if the workforce does not use data-driven decision-making. Another common AI implementation problem is a lack of change management. ",[],{"_key":24590,"_type":99,"children":24591,"markDefs":24595,"style":799},"7yYS2F_5OJ8zHJsby2ihP",[24592],{"_type":103,"marks":24593,"text":24594},[],"Artificial intelligence (AI) frequently requires considerable changes in organizational structure and strategy, as well as personnel attitudes and abilities. As a result, companies should make the change of management a key aspect of any AI deployment strategy, and make sure the company’s leaders have the skills and motivation to develop an AI-centric culture.",[],{"_key":24597,"_type":99,"children":24598,"markDefs":24602,"style":170},"sOCaLJ8tqmreJ808SI64Q",[24599],{"_type":103,"marks":24600,"text":24601},[],"While it is tempting to construct large-scale AI systems, focusing on low-hanging fruit is typically a better strategy",[],{"_key":24604,"_type":99,"children":24605,"markDefs":24609,"style":799},"hn_qsZj7dofMC-KknagGA",[24606],{"_type":103,"marks":24607,"text":24608},[],"It could be a good idea for a company to first start with robotic process automation (RPA), which is less expensive than AI and has a faster return on investment. RPA is non-invasive, which means it does not disturb the flow of existing systems as many AI solutions do. ",[],{"_key":24611,"_type":99,"children":24612,"markDefs":24616,"style":799},"IoqVJetRxpiT_F6lpkbJx",[24613],{"_type":103,"marks":24614,"text":24615},[],"Small steps and wins in AI initiatives can also assist justify more ambitious AI expenditures and guarantee stakeholder buy-in in the future.",[],{"_key":24618,"_type":99,"children":24619,"markDefs":24623,"style":170},"jEYDDKaGOVdV-nUbKg4lq",[24620],{"_type":103,"marks":24621,"text":24622},[],"How to define proper objectives when it comes to AI deployment.",[],{"_key":24625,"_type":99,"children":24626,"markDefs":24630,"style":799},"0RIHbxBO2QJ8N-hUdro_6",[24627],{"_type":103,"marks":24628,"text":24629},[],"Clear expectations regarding the consequences of an AI program are critical. End users seldom participate actively in AI initiatives, so when the technical team creates faultless AI systems, they add minimal value to the business. Therefore, it is vital to include all stakeholders in the project from the start.",[],{"_key":24632,"_type":99,"children":24633,"markDefs":24637,"style":799},"1WnrGYvWnl04FcBic9MOC",[24634],{"_type":103,"marks":24635,"text":24636},[],"Furthermore, AI initiatives frequently provide benefits that cannot be quantified. Improved employee happiness or a better customer experience, for example, is significantly more difficult to monitor than cost or time savings. Let’s imagine a company wants to develop an AI solution to help the IT staff categorize tickets faster. First, because the system will have to decipher free-form text using natural language processing, it will not be perfect at the very beginning. As a result, the team will need to calculate the acceptable mistake rate and factor it into the ROI calculation.",[],{"_key":24639,"_type":99,"children":24640,"markDefs":24644,"style":799},"inGsXJM2pQ8RRiTENBaYN",[24641],{"_type":103,"marks":24642,"text":24643},[],"In addition, if there is a major issue that requires quick attention from IT workers, and an AI system incorrectly classifies the ticket as low priority, this will complicate ROI calculations because it is difficult to quantify the negative consequences of such a situation. Hence, it is crucial to start with initiatives that can be adequately quantified in terms of ROI. Many industrial organizations, for example, are able to achieve economic returns on AI quality control programs since their ROI is quite simple to calculate.",[],{"_key":24646,"_type":99,"children":24647,"markDefs":24651,"style":170},"Sa7dv5X2_opxygO_Az_Au",[24648],{"_type":103,"marks":24649,"text":24650},[],"To conclude, the AI implementation journey requires high AI maturity and a great focus on business analysis.",[],{"_key":24653,"_type":99,"children":24654,"markDefs":24658,"style":799},"b0xu4B0YHNBzqzaHA5XUT",[24655],{"_type":103,"marks":24656,"text":24657},[],"So, how to get returns from AI investments? Generally, firms that are more mature and experienced have a higher chance of benefiting from AI. Data governance standards, sophisticated training programs, performance monitoring systems, and specific project goals are common features of such businesses. These are significant distinctions between firms that thrive and those that fail when it comes to AI deployment. ",[],{"_key":24660,"_type":99,"children":24661,"markDefs":24677,"style":799},"0xkPm3aEnCZ4OvAxAY8MW",[24662,24665,24669,24672,24675],{"_type":103,"marks":24663,"text":24664},[],"Given the unpredictability of project success rates, AI, more than any other technology, needs a strong foundation in key management areas. The ability of a company to track, measure, and manage operations is typically linked to its likelihood of benefitting from AI. Do you need help with your AI implementation? 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This transformation is so compelling that it has been named “Industry 4.0” to signify the fourth manufacturing revolution. The first industrial revolution identified by water and steam power was just the beginning of a long ongoing process. The second revolution followed with mass production and assembly lines using electricity. After decades of development, the fourth industrial revolution is just around the corner. Industry 4.0 will build on what was started in the third revolution with the adoption of computers and automation by adding smart and autonomous systems powered by data and machine learning. ",[],{"_key":25144,"_type":99,"children":25145,"markDefs":25149,"style":170},"auJYkR-zjPjrqrXWwT9Tg",[25146],{"_type":103,"marks":25147,"text":25148},[],"What is Industry 4.0?",[],{"_key":25151,"_type":99,"children":25152,"markDefs":25156,"style":799},"MFsIaI50TzkNoCNN3SbbD",[25153],{"_type":103,"marks":25154,"text":25155},[],"Industry 4.0 is the digital transformation of the value chain and manufacturing processes. The core of Industry 4.0 are cyber-physical systems, such as “smart machines.” They have implemented software systems and modern control technologies that keep them connected to Internet addresses. By doing this, production processes get networked and can communicate to optimize work in real-time, as well as enable new ways of production. Such smart machines are the fuel of smart factories as they boost capabilities from the Industrial Internet of Things – remote monitoring, and track and trace. ",[],{"_key":25158,"_type":99,"children":25159,"markDefs":25163,"style":170},"j9cZvogeQ6jGg9RIsY18b",[25160],{"_type":103,"marks":25161,"text":25162},[],"Main Characteristics of Industry 4.0",[],{"_key":25165,"_type":99,"children":25166,"markDefs":25170,"style":799},"PGyLLn1KlqGMRoPH1szEq",[25167],{"_type":103,"marks":25168,"text":25169},[],"To better understand the notion of the fourth revolution, there are some specifics that make it different from the previous three revolutions:",[],{"_key":25172,"_type":99,"children":25173,"level":230,"listItem":231,"markDefs":25177,"style":107},"nyVSog8JP9M28AKiWDPwQ",[25174],{"_type":103,"marks":25175,"text":25176},[],"Automation, which is developed to a next level in contrast with the third revolution;",[],{"_key":25179,"_type":99,"children":25180,"level":230,"listItem":231,"markDefs":25184,"style":107},"feA7bBSJtwIr9xZV7Jrej",[25181],{"_type":103,"marks":25182,"text":25183},[],"Data exchange in control systems – the cyber-physical systems, enabled by Industrial IoT;",[],{"_key":25186,"_type":99,"children":25187,"level":230,"listItem":231,"markDefs":25191,"style":107},"RyckJ6Zf9AoID9MSnIREH",[25188],{"_type":103,"marks":25189,"text":25190},[],"One smart system where smart products define the production processes and steps rather than a central industrial control system;",[],{"_key":25193,"_type":99,"children":25194,"level":230,"listItem":231,"markDefs":25198,"style":107},"4lkdKSyXX9yV_U72C4qfx",[25195],{"_type":103,"marks":25196,"text":25197},[],"Personalized products.",[],{"_key":25200,"_type":99,"children":25201,"markDefs":25205,"style":799},"3HlWcddEucrpdnJMAhWlw",[25202],{"_type":103,"marks":25203,"text":25204},[],"Fundamentally, the technologies that enable it make use of existing data and new data sources, creating a smooth flow of information across the value chain. This corresponds to data from connected assets which results in efficiencies on multiple levels and transforming existing manufacturing processes. ",[],{"_key":25207,"_type":99,"children":25208,"markDefs":25212,"style":170},"C54O0T6OaHJDuxO4MoZNB",[25209],{"_type":103,"marks":25210,"text":25211},[],"Application of Industry 4.0",[],{"_key":25214,"_type":99,"children":25215,"markDefs":25219,"style":799},"nnFP5meJWHKjdavfblpog",[25216],{"_type":103,"marks":25217,"text":25218},[],"The use of smart machines can improve businesses in several different cases:",[],{"_key":25221,"_type":99,"children":25222,"markDefs":25226,"style":170},"y7-njDKm46JVT4NUHOcnn",[25223],{"_type":103,"marks":25224,"text":25225},[],"Internet of Things and the Cloud",[],{"_key":25228,"_type":99,"children":25229,"markDefs":25233,"style":799},"nzsCtkc0gFL6xiG9KPHg3",[25230],{"_type":103,"marks":25231,"text":25232},[],"As it was mentioned above, IoT is an essential characteristic of industry 4.0. It aids internal operations by storing data in a cloud. Thus, equipment and operations could be optimized by utilizing the knowledge of others who use the same equipment. As a result, even small enterprises can access technologies they would not be able to on their own.",[],{"_key":25235,"_type":99,"children":25236,"markDefs":25240,"style":170},"46MNEXUU61JBWZ0urDtT1",[25237],{"_type":103,"marks":25238,"text":25239},[],"Opportunities Identification",[],{"_key":25242,"_type":99,"children":25243,"markDefs":25253,"style":799},"_095Mj9g-sPWWDk67AoXi",[25244,25247,25250],{"_type":103,"marks":25245,"text":25246},[],"Since data is collected from sensors of connected machines, it could warn maintenance and performance teams in advance of possible errors. You can learn about the concept of Predictive Maintenance in our ",{"_type":103,"marks":25248,"text":72},[25249],"XVNzdUa8F93mcvV4cY_Sr",{"_type":103,"marks":25251,"text":25252},[],". Usually, this information could be acquired by a human; the technology analyzes and identifies patterns that guarantee enough time for reaction. Industry 4.0 helps manufacturers increase efficiency by showing them what needs attention.",[25254],{"_key":25249,"_type":173,"href":22826},{"_key":25256,"_type":99,"children":25257,"markDefs":25261,"style":170},"sezFxozRH8K86ofxRToJT",[25258],{"_type":103,"marks":25259,"text":25260},[],"Optimization of Logistics and Supply Chain",[],{"_key":25263,"_type":99,"children":25264,"markDefs":25268,"style":799},"oiXrdm_9_RnKr1MAvJEJL",[25265],{"_type":103,"marks":25266,"text":25267},[],"When new information is supplied, a connected supply chain may modify and accommodate accordingly. For example, if a shipment is delayed due to weather, a networked system can anticipate the situation and adapt manufacturing priorities.",[],{"_key":25270,"_type":99,"children":25271,"markDefs":25275,"style":170},"62H9OAiGkxMqM4crscJuG",[25272],{"_type":103,"marks":25273,"text":25274},[],"The Future of Industry 4.0",[],{"_key":25277,"_type":99,"children":25278,"markDefs":25282,"style":799},"6JyGhxjIZAgbEbjPGACDR",[25279],{"_type":103,"marks":25280,"text":25281},[],"Although there are plenty of benefits that the next industrial revolution carries with it, the world is still on the entering stage of adapting its novelties. Many businesses around the world have already acknowledged the potential of smart machines but there is still room for improvement. Industry 4.0 is the digital transformation of manufacturing. However, the concept requires some more experience and time to become fully acceptable by business owners",[],{"_key":25284,"_type":99,"children":25285,"markDefs":25296,"style":799},"f36P-L5N_OICadouyXPbL",[25286,25289,25293],{"_type":103,"marks":25287,"text":25288},[],"Do you want to revolutionalize your manufacturing business? ",{"_type":103,"marks":25290,"text":25292},[25291],"-H8VsRSMtxRzbhPQRey5z","Book a free meeting",{"_type":103,"marks":25294,"text":25295},[]," and let us help you achieve that goal!",[25297],{"_key":25291,"_type":173,"href":19536},{"_type":17,"current":25128},[25300,25301],{"_createdAt":20710,"_id":20711,"_rev":20712,"_type":8636,"_updatedAt":20713,"name":20714,"orderRank":15218,"uid":20715},{"_createdAt":22144,"_id":22145,"_rev":22146,"_type":8636,"_updatedAt":22147,"name":22148,"orderRank":15683,"uid":22149},{"_createdAt":25303,"_id":25304,"_rev":25305,"_system":25306,"_type":72,"_updatedAt":25309,"archived":126,"author":161,"category":25310,"date":25314,"description":25315,"image":161,"name":25324,"oldSlug":25325,"orderRank":25326,"reviewer":161,"sections":25327,"seo":161,"slug":25556,"tags":25557},"2026-01-15T15:57:06Z","22b792dc-35ee-4b38-ac5c-4db0b6fa1686","3x1HJiv3wwU7cYVoHtNvaM",{"base":25307},{"id":25304,"rev":25308},"ZfaOePOqVJD5r4KHzTTLKv","2026-01-28T08:45:03Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":25311,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":25313,"uid":54},{"base":25312},{"id":45,"rev":49},{"_type":17,"current":54},"2022-12-12",[25316],{"_key":25317,"_type":99,"children":25318,"markDefs":25323,"style":107},"a76f893e3ecf",[25319],{"_key":25320,"_type":103,"marks":25321,"text":25322},"566a6139a5cc",[],"In more recent years Artificial Intelligence (AI) and Machine Learning (ML) have been on a conquest to change the face of numerous industries, and the",[],"How AI and ML can unleash the potential of Manufacturing","how-ai-and-ml-can-unleash-manufacturing","0|1000go:",[25328],{"_createdAt":25329,"_id":25330,"_key":25331,"_ref":25330,"_rev":25308,"_type":168,"_updatedAt":25329,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":25332,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:48Z","JxFvx1-EFVvGohI7AsD0J","fxrxf7k7rJzH5qzjzkgBN",[25333,25352,25359,25366,25373,25380,25387,25394,25401,25408,25415,25422,25429,25436,25443,25459,25466,25473,25480,25486,25493,25500,25507,25514,25521,25527],{"_key":25334,"_type":99,"children":25335,"markDefs":25349,"style":799},"itcjRo6WuszGW9cDZsaoN",[25336,25339,25342,25346],{"_type":103,"marks":25337,"text":25338},[],"In more recent years Artificial Intelligence (AI) and Machine Learning (ML) have been on a conquest to change the face of numerous industries, and the Manufacturing industry is no exception.",{"_type":103,"marks":25340,"text":25341},[],"As this sector is the backbone of any economy, it is easy to see why the changes brought on are important to comprehend anyone and why ",{"_type":103,"marks":25343,"text":25345},[25344],"xK2qTPbrzjnxF8bCIt8df","85% of executives believe",{"_type":103,"marks":25347,"text":25348},[]," AI could give their companies a strong advantage. How AI and ML can unleash manufacturing?",[25350],{"_key":25344,"_type":173,"href":25351},"https://www.tandfonline.com/doi/full/10.1080/21693277.2016.1192517",{"_key":25353,"_type":99,"children":25354,"markDefs":25358,"style":170},"sn1eUn1OgcODBskn3SaIi",[25355],{"_type":103,"marks":25356,"text":25357},[],"The benefits",[],{"_key":25360,"_type":99,"children":25361,"markDefs":25365,"style":799},"RxHAA2EqPAci6ramkYhRD",[25362],{"_type":103,"marks":25363,"text":25364},[],"Let us start with outlining the benefits that AI and ML bring to the table",[],{"_key":25367,"_type":99,"children":25368,"level":230,"listItem":231,"markDefs":25372,"style":107},"HOsciNqGXbMcPiWq5URqz",[25369],{"_type":103,"marks":25370,"text":25371},[],"Improvements in workplace safety;",[],{"_key":25374,"_type":99,"children":25375,"level":230,"listItem":231,"markDefs":25379,"style":107},"wLUurhQ7sObwD9Lo289el",[25376],{"_type":103,"marks":25377,"text":25378},[],"Easier Machine Maintenance;",[],{"_key":25381,"_type":99,"children":25382,"level":230,"listItem":231,"markDefs":25386,"style":107},"-Ub49_keIL8D77jXtwa__",[25383],{"_type":103,"marks":25384,"text":25385},[],"Greater Cybersecurity;",[],{"_key":25388,"_type":99,"children":25389,"level":230,"listItem":231,"markDefs":25393,"style":107},"-FgF19i0yK2eh95bys-rz",[25390],{"_type":103,"marks":25391,"text":25392},[],"Increased Productivity;",[],{"_key":25395,"_type":99,"children":25396,"level":230,"listItem":231,"markDefs":25400,"style":107},"B1k-O69x4MBNdMnVN9UvF",[25397],{"_type":103,"marks":25398,"text":25399},[],"Easier product Development;",[],{"_key":25402,"_type":99,"children":25403,"level":230,"listItem":231,"markDefs":25407,"style":107},"p3Od3V56bwxLJ1bwh1avX",[25404],{"_type":103,"marks":25405,"text":25406},[],"Robotics Development;",[],{"_key":25409,"_type":99,"children":25410,"level":230,"listItem":231,"markDefs":25414,"style":107},"C1-OHzK4LqVudgM1y7xOd",[25411],{"_type":103,"marks":25412,"text":25413},[],"Better Decision Making.",[],{"_key":25416,"_type":99,"children":25417,"markDefs":25421,"style":170},"ns42iN3ayigZ3_CR-GruK",[25418],{"_type":103,"marks":25419,"text":25420},[],"Let’s dive deeper:",[],{"_key":25423,"_type":99,"children":25424,"markDefs":25428,"style":170},"Q6lhdfWP3ZaWujC7LZ_08",[25425],{"_type":103,"marks":25426,"text":25427},[],"Safety:",[],{"_key":25430,"_type":99,"children":25431,"markDefs":25435,"style":799},"k4Y_3dVp-fTQK_7x8QFuT",[25432],{"_type":103,"marks":25433,"text":25434},[],"How do AI and ML affect safety? Employee entry can be easily monitored and controlled without the help of other staff. Additionally, staff that is already present can also be monitored thus ensuring the safety of the premises. In the current COVID-19 pandemic, this proves to be especially helpful time and time again. Effective tracing of the spreading of the virus inside of the premises of the business can be seamlessly executed and more spreading can be prevented. AI can also identify potential risk areas, or, in the aftermath of an incident, a root cause analysis can be provided.",[],{"_key":25437,"_type":99,"children":25438,"markDefs":25442,"style":170},"ErklzgIh5vt-dWb-TV8MP",[25439],{"_type":103,"marks":25440,"text":25441},[],"Machine Maintenance:",[],{"_key":25444,"_type":99,"children":25445,"markDefs":25456,"style":799},"7BqLttFS4x0oQAcnsJcwJ",[25446,25449,25453],{"_type":103,"marks":25447,"text":25448},[],"When it comes to Machine Maintenance, proper integration of AI and ML can enable predictive maintenance. ",{"_type":103,"marks":25450,"text":25452},[25451],"kY-TR17Kz9NZwRNUKeZ4C","McKinsey",{"_type":103,"marks":25454,"text":25455},[]," finds that predictive maintenance can generate a value of between 0.5 billion to 0.7 billion dollars across the globe. Based on information from data and sensors, equipment failures can be accurately predicted, thus saving the company time and money in the long run by reducing downtime, in fact, companies save close to 30% of costs this way. ",[25457],{"_key":25451,"_type":173,"href":25458},"https://www.mckinsey.com/~/media/mckinsey/industries/advanced%20electronics/our%20insights/how%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/mgi-artificial-intelligence-discussion-paper.ashx",{"_key":25460,"_type":99,"children":25461,"markDefs":25465,"style":799},"fSKFlY2GpjRsojJrQ5_yM",[25462],{"_type":103,"marks":25463,"text":25464},[],"A major firm in the Manufacturing sector reported on a profit improvement of around 300 million euro by using ML to forecast 10 years of repairs needed for their fleet of over 17,000 aircrafts.",[],{"_key":25467,"_type":99,"children":25468,"markDefs":25472,"style":170},"cGHBfN2jyRrHFdOTM02oU",[25469],{"_type":103,"marks":25470,"text":25471},[],"Cybersecurity:",[],{"_key":25474,"_type":99,"children":25475,"markDefs":25479,"style":799},"jnZKcTyglNHbrYhrzOwfQ",[25476],{"_type":103,"marks":25477,"text":25478},[],"Companies that integrate AI and ML can easily recognize cybersecurity improvements. Moreover, in today’s day and age manufacturing companies produce vast amounts of data, which raises the need for better security. In data-rich environments, with cybersecurity being one of the lowest budget areas of any business, AI can scan through a vast number of records, identifying gaps and loopholes that are vulnerable, enabling easy mending of the issues.",[],{"_key":25481,"_type":99,"children":25482,"markDefs":25485,"style":170},"gWLpZaQjRDoL52rSj-LWX",[25483],{"_type":103,"marks":25484,"text":17755},[],[],{"_key":25487,"_type":99,"children":25488,"markDefs":25492,"style":799},"PAfGDDLxD0Y3pBM8iu7O3",[25489],{"_type":103,"marks":25490,"text":25491},[],"Detailed analysis of patterns in various data can enhance productivity – from performance data to sensor data, and anything else a business is tracking. For example, areas where resources are wasted, and productivity can be enhanced are clearly flagged. ",[],{"_key":25494,"_type":99,"children":25495,"markDefs":25499,"style":170},"WnI_i40fff8dZZhs3zIao",[25496],{"_type":103,"marks":25497,"text":25498},[],"Development:",[],{"_key":25501,"_type":99,"children":25502,"markDefs":25506,"style":799},"NLsEdZXRmLslypwKoK8gB",[25503],{"_type":103,"marks":25504,"text":25505},[],"Developing products using painstaking amounts of time and resources is made redundant by AI and ML. This allows to create a perfect digital copy of a concept, and a business can test any and all features and possibilities virtually. This not only saves time but speeds up development by an astounding amount. It also enables testing in environments never accessible before, allowing for potentially discovering new features of a product. General Electric (NYSE: GE) gained a 12% improvement in the efficiency of the airplanes they produced by taking advantage of an algorithm that designed flight planning.",[],{"_key":25508,"_type":99,"children":25509,"markDefs":25513,"style":170},"VD8anJvbR2Uc7vCWWuHZD",[25510],{"_type":103,"marks":25511,"text":25512},[],"Robotics",[],{"_key":25515,"_type":99,"children":25516,"markDefs":25520,"style":799},"VqCa6T9vknUgKlyU9ZN4g",[25517],{"_type":103,"marks":25518,"text":25519},[],"Robotics as a field has aided manufacturing since its conception. The robots are capable of working in strenuous conditions, 24 hours a day, 7 days a week, with the only downtime being when the robot breaks down. The predictive maintenance mentioned above can help with that too.",[],{"_key":25522,"_type":99,"children":25523,"markDefs":25526,"style":170},"Xcgr51cm7SM7xcJ9V6xgf",[25524],{"_type":103,"marks":25525,"text":4733},[],[],{"_key":25528,"_type":99,"children":25529,"markDefs":25551,"style":799},"Pnh6WTwFSqyG2nkQityOD",[25530,25533,25537,25540,25543,25546,25549],{"_type":103,"marks":25531,"text":25532},[],"In a nutshell, experts ",{"_type":103,"marks":25534,"text":25536},[25535],"iXlGWe9jCZCPgP4_7UOEu","predict",{"_type":103,"marks":25538,"text":25539},[]," that AI and ML will play major roles in the future of manufacturing. Additionally, Their integration is a major hurdle for many businesses. We at ",{"_type":103,"marks":25541,"text":7898},[25542],"EQzgmxAr-rl-uLs7SMs49",{"_type":103,"marks":25544,"text":25545},[]," specialize in adapting and implementing these technologies to our client’s needs. Learn more about how AI and ML can unleash manufacturing or about our other services ",{"_type":103,"marks":25547,"text":4754},[25548],"v8oRhGXGE2agKCnpzJAIw",{"_type":103,"marks":25550,"text":793},[],[25552,25554,25555],{"_key":25535,"_type":173,"href":25553},"https://spectator.sme.sk/c/22750732/six-examples-of-how-artificial-intelligence-is-used-in-manufacturing.html",{"_key":25542,"_type":173,"href":18723},{"_key":25548,"_type":173,"href":19377},{"_type":17,"current":25325},[25558,25559,25560],{"_createdAt":20710,"_id":20711,"_rev":20712,"_type":8636,"_updatedAt":20713,"name":20714,"orderRank":15218,"uid":20715},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":22144,"_id":22145,"_rev":22146,"_type":8636,"_updatedAt":22147,"name":22148,"orderRank":15683,"uid":22149},{"_createdAt":25562,"_id":25563,"_rev":25564,"_system":25565,"_type":72,"_updatedAt":25568,"archived":126,"author":161,"category":25569,"date":25314,"description":25573,"image":161,"name":25582,"oldSlug":25583,"orderRank":25584,"reviewer":161,"sections":25585,"seo":161,"slug":25730,"tags":25731},"2026-01-15T15:56:36Z","8f40322b-8d78-4c26-a800-eba28d52f148","3x1HJiv3wwU7cYVoHtOQUU",{"base":25566},{"id":25563,"rev":25567},"ZfaOePOqVJD5r4KHzTTKzI","2026-01-28T08:45:42Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":25570,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":25572,"uid":54},{"base":25571},{"id":45,"rev":49},{"_type":17,"current":54},[25574],{"_key":25575,"_type":99,"children":25576,"markDefs":25581,"style":107},"92fd6127cb17",[25577],{"_key":25578,"_type":103,"marks":25579,"text":25580},"68fe85cf3152",[],"Despite its key role in creating and adapting the spaces in which we live and work, the construction industry has continued to rely primarily on",[],"Building a better future: AI and robots in the construction industry","building-a-better-future-ai-and-robots-in-the-construction-industry","0|1000g8:",[25586],{"_createdAt":25587,"_id":25588,"_key":25589,"_ref":25588,"_rev":25567,"_type":168,"_updatedAt":25587,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":25590,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:47Z","uV-6E787xkn1tcYz5hRHb","28LEs_avPinQ8M9KgoqiY",[25591,25598,25605,25621,25628,25635,25642,25649,25656,25663,25679,25686,25693,25700,25707,25714,25721],{"_key":25592,"_type":99,"children":25593,"markDefs":25597,"style":799},"dYhlyA_7x-fUfHbUMDN8v",[25594],{"_type":103,"marks":25595,"text":25596},[],"Despite its key role in creating and adapting the spaces in which we live and work, the construction industry has continued to rely primarily on manual labour, with little to no automation. While there have been many important advances in robotics and AI over the last decade, construction has lagged behind other sectors in introducing automation on a large scale. Therefore, let’s take a look at the role of AI and robots in the construction industry.",[],{"_key":25599,"_type":99,"children":25600,"markDefs":25604,"style":170},"EE7MpMBhkQroz8jEd_gpd",[25601],{"_type":103,"marks":25602,"text":25603},[],"AI and robots in the construction industry",[],{"_key":25606,"_type":99,"children":25607,"markDefs":25618,"style":799},"btnBVn3aTsRu_7UigH5Rk",[25608,25611,25615],{"_type":103,"marks":25609,"text":25610},[],"According to a ",{"_type":103,"marks":25612,"text":25614},[25613],"kEzm9To3TbpLqVuaCUvY7","survey",{"_type":103,"marks":25616,"text":25617},[]," commissioned by robotics firm, ABB, 91% of construction businesses in Europe are predicting a skills crisis by 2030. The shift will inevitably boost interest in this area and drive the application of robots and other automated solutions.",[25619],{"_key":25613,"_type":173,"href":25620},"https://www.viatechnik.com/how-far-away-is-constructions-automated-future/",{"_key":25622,"_type":99,"children":25623,"markDefs":25627,"style":799},"zEuTlUcJcy6oCgaEaMkLD",[25624],{"_type":103,"marks":25625,"text":25626},[],"However, there are obstacles hindering the use and adoption of AI and robotics in the construction industry. One of them is the sheer unpredictability of construction sites. While robots excel at repetitive tasks, a construction site requires adaptability and flexibility. It is more technically feasible to automate predictable physical activities than unpredictable ones. ",[],{"_key":25629,"_type":99,"children":25630,"markDefs":25634,"style":170},"2QVLT77Or89Na8-V378s-",[25631],{"_type":103,"marks":25632,"text":25633},[],"Construction robots and their applications",[],{"_key":25636,"_type":99,"children":25637,"markDefs":25641,"style":799},"NUVB86N-8Og-5cIkCmZWP",[25638],{"_type":103,"marks":25639,"text":25640},[],"Below are some examples of construction robots and the range of activities they can undertake on-site:",[],{"_key":25643,"_type":99,"children":25644,"markDefs":25648,"style":170},"6vX48mtA-hzLE-I3nyDfG",[25645],{"_type":103,"marks":25646,"text":25647},[],"Housebuilding accelerated",[],{"_key":25650,"_type":99,"children":25651,"markDefs":25655,"style":799},"40vv0Cy6hr6pvd2v1DJZO",[25652],{"_type":103,"marks":25653,"text":25654},[],"Hadrian X is an automated bricklaying machine capable of building the walls of a house by calculating the required materials and movements without any supervision. Developed by an Australian firm by incorporating an intelligent control system, the robot can lay bricks at a speed of 1,000 per hour with 100% accuracy. It can also detect changes caused by external factors such as wind and vibrations and adapt the design accordingly. It has been estimated that the robot takes two days to complete work that, when done manually, could otherwise take around four to six weeks!",[],{"_key":25657,"_type":99,"children":25658,"markDefs":25662,"style":170},"PWzMKMklr9ouddieuz9XS",[25659],{"_type":103,"marks":25660,"text":25661},[],"Making construction safer",[],{"_key":25664,"_type":99,"children":25665,"markDefs":25676,"style":799},"A6UzNpwAvKO8zobEGwlYE",[25666,25669,25673],{"_type":103,"marks":25667,"text":25668},[],"Another important way in which the application of AI and robotics can enhance the construction industry is in accident prevention. Sadly, construction continues to be one of the most dangerous industries for workers. ",{"_type":103,"marks":25670,"text":25672},[25671],"g9-FHQsn8jQg1sTgTeZOD","In 2018",{"_type":103,"marks":25674,"text":25675},[],", it presented the highest number of fatal worksite injuries in the USA – 20% of all workplace fatalities.",[25677],{"_key":25671,"_type":173,"href":25678},"https://www.automate.org/industry-insights/3-ways-robots-are-making-construction-safer",{"_key":25680,"_type":99,"children":25681,"markDefs":25685,"style":170},"iB8Z8UCm9zpHYtKFTARm-",[25682],{"_type":103,"marks":25683,"text":25684},[],"Enhanced design and engineering",[],{"_key":25687,"_type":99,"children":25688,"markDefs":25692,"style":799},"z4vv8PZjFvU3oofjKZugw",[25689],{"_type":103,"marks":25690,"text":25691},[],"While most research focuses on the actual delivery of projects in the construction sector, there are many applications of AI within the other phases of project development, such as architectural design and structural engineering. These areas are less dependent on physical work and are relatively easier to empower through AI solutions.",[],{"_key":25694,"_type":99,"children":25695,"markDefs":25699,"style":170},"aDugCTafg7nkG2TMbnbec",[25696],{"_type":103,"marks":25697,"text":25698},[],"Constructing a better future together",[],{"_key":25701,"_type":99,"children":25702,"markDefs":25706,"style":799},"6vCTm2EywevMtiYUgZRk4",[25703],{"_type":103,"marks":25704,"text":25705},[],"While we’re currently at tipping point, we believe that AI will inevitably take over construction by becoming more integrated into the software and equipment used by the industry and its related disciplines. ",[],{"_key":25708,"_type":99,"children":25709,"markDefs":25713,"style":799},"Q4-NbiGB5n_t5E7cZm0XF",[25710],{"_type":103,"marks":25711,"text":25712},[],"However, as the development of computers didn’t remove the need for accounting firms, AI will enhance rather than replace the construction industry. It will achieve this by making construction safer and more effective and introducing greater co-operation between people and machines.",[],{"_key":25715,"_type":99,"children":25716,"markDefs":25720,"style":799},"jCHbDeY4HddeZe8XPvGhG",[25717],{"_type":103,"marks":25718,"text":25719},[3055],"At Cosmos Thrace, we enable businesses from many sectors to implement AI Solutions and optimize their business operations. Through our expertise, we adapt those technologies to each customer’s specific needs, requirements, and priorities in an efficient and timely manner.",[],{"_key":25722,"_type":99,"children":25723,"markDefs":25728,"style":799},"r_27s5RDazf_kAL4wfqGp",[25724],{"_type":103,"marks":25725,"text":25727},[3055,25726],"4Hf6dgJpJ1t3Y_sVEFhYo","Learn how to enable AI in your business.",[25729],{"_key":25726,"_type":173,"href":19377},{"_type":17,"current":25583},[25732,25733,25734],{"_createdAt":20710,"_id":20711,"_rev":20712,"_type":8636,"_updatedAt":20713,"name":20714,"orderRank":15218,"uid":20715},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":22144,"_id":22145,"_rev":22146,"_type":8636,"_updatedAt":22147,"name":22148,"orderRank":15683,"uid":22149},{"_createdAt":25736,"_id":25737,"_rev":25738,"_system":25739,"_type":72,"_updatedAt":25742,"archived":126,"author":161,"category":25743,"date":25314,"description":25747,"image":161,"name":25756,"oldSlug":25757,"orderRank":25758,"reviewer":161,"sections":25759,"seo":161,"slug":25870,"tags":25871},"2026-01-15T15:58:05Z","990e3150-6ca9-43fb-8fc6-a99499850701","fQbvJUaqxAsdnxoHr5jHiA",{"base":25740},{"id":25737,"rev":25741},"YkA36qTDOerM1fSJamXunA","2026-01-26T13:28:10Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":25744,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":25746,"uid":66},{"base":25745},{"id":57,"rev":61},{"_type":17,"current":66},[25748],{"_key":25749,"_type":99,"children":25750,"markDefs":25755,"style":107},"05f5de2d473b",[25751],{"_key":25752,"_type":103,"marks":25753,"text":25754},"37bad2ac7296",[],"The technology giants Google, DeepMind, and Amazon Web Services are entering with serious investments of 7 million dollars in total in the first of its",[],"Bulgaria took the first step toward becoming the leader in Eastern Europe in Artificial Intelligence and Computer Science","bulgaria-took-the-first-step-toward-becoming-the-leader-in-eastern-europe-in-artificial-intelligence-and-computer-science","0|1000hk:",[25760],{"_createdAt":25761,"_id":25762,"_key":25763,"_ref":25762,"_rev":25764,"_system":25765,"_type":168,"_updatedAt":25767,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":25768,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:52Z","8jhsK584v9Gcxw8ClYXok","SnF7ZeM7z9qVKMTfjZJTo","lmjyWiJ0RL9BacmzRF2srX",{"base":25766},{"id":25762,"rev":25741},"2026-01-26T13:28:09Z",[25769,25777,25784,25792,25799,25807,25814,25822,25830,25838,25846,25854,25862],{"_key":25770,"_type":99,"children":25771,"markDefs":25776,"style":799},"ientOB7NBfGJtfSswzMuL",[25772],{"_key":25773,"_type":103,"marks":25774,"text":25775},"cfd14ffe37ef",[],"The technology giants Google, DeepMind, and Amazon Web Services are entering with serious investments of 7 million dollars in total in the first of its kind Bulgarian Institute of Computer Science and Artificial Intelligence INSAIT. The institute was officially opened on April 11, 2022, at a special event at the National Palace of Culture. ",[],{"_key":25778,"_type":99,"children":25779,"markDefs":25783,"style":107},"a1468bfd9c3f",[25780],{"_key":25781,"_type":103,"marks":25782,"text":4420},"dfa329083ccd",[],[],{"_key":25785,"_type":99,"children":25786,"markDefs":25791,"style":799},"t9i2hVLY9k0EysGn9tgBl",[25787],{"_key":25788,"_type":103,"marks":25789,"text":25790},"318ef7e31f4e",[],"Not only that but the institute was established and will work in partnership with the two largest technological universities in Switzerland – the Federal Institute of Technology in Zurich (ETH Zurich) and the Polytechnic University of Lausanne (EPFL) and will be led by world-renowned scientists, Bulgarians and foreigners of the best universities in the United States and Israel.",[],{"_key":25793,"_type":99,"children":25794,"markDefs":25798,"style":107},"55c2f9b2190b",[25795],{"_key":25796,"_type":103,"marks":25797,"text":4420},"b7deb8169fbb",[],[],{"_key":25800,"_type":99,"children":25801,"markDefs":25806,"style":799},"9PmXl0v3O7ZUyAp7TSyja",[25802],{"_key":25803,"_type":103,"marks":25804,"text":25805},"4f7e5e27e787",[],"The goals of INSAIT are for Bulgaria to become the best place in the world in the field of computer science and artificial intelligence. The aim of Bulgaria is  to attract the largest companies in the world and open their research centers in the country, according to the Prime Minister of Bulgaria, Kiril Petkov. In addition to the first foreign investments announced so far by the American technology giants, the state and Bulgarian businesses are involved in the long-term financing of the institute in unprecedented cooperation. Bulgaria will invest 10 million in INSAIT in each of the coming years and Bulgarian technology companies, led by SiteGround, are also involved with a $ 6m investment.",[],{"_key":25808,"_type":99,"children":25809,"markDefs":25813,"style":107},"08fa06c7b8ba",[25810],{"_key":25811,"_type":103,"marks":25812,"text":4420},"9ec2601c143c",[],[],{"_key":25815,"_type":99,"children":25816,"markDefs":25821,"style":799},"P3bCT8Zkxs2zz9faFfwD0",[25817],{"_key":25818,"_type":103,"marks":25819,"text":25820},"3818ef17d964",[],"INSAIT has the ambition and potential to establish itself as one of the world’s leading research and education centers, providing for the first time working conditions comparable to those in Western universities. The institute will develop its activity under the auspices of Sofia University “St. Kliment Ohridski.” Behind the creation of this center is the great idea of promoting economic growth through education. INSAIT has the potential not only to attract world-class scientists to Bulgaria but also to keep its valuable young minds in the country.",[],{"_key":25823,"_type":99,"children":25824,"markDefs":25829,"style":799},"HhDzxNJDYEKl7xDak_uPF",[25825],{"_key":25826,"_type":103,"marks":25827,"text":25828},"a15b09e7756d",[],"The realization of the first high-tech research center of its kind in Bulgaria was a dream of more than a decade ago by a graduate student at that time in Cambridge. Subsequently, he became one of the most successful and award-winning Bulgarian scientists in the field of computer science and artificial intelligence, and at the opening, he was presented as the ideological architect of INSAIT – Prof. Martin Vechev.",[],{"_key":25831,"_type":99,"children":25832,"markDefs":25837,"style":799},"98xOLFmgrTCnnR7W4QoRs",[25833],{"_key":25834,"_type":103,"marks":25835,"text":25836},"6a475721f4b9",[]," “When I started my postgraduate studies in Cambridge years ago and applied for a scholarship, there was a question on the form: ‘What do you want to achieve in 20-30 years?,’ said Prof. Vechev. “I wrote that I dream of creating a world-class research center like Cambridge. This dream is already a fact and when you leave this opening ceremony and you are asked what happened at this event, say that for the first time in Bulgaria there is a place that allows anyone who wants to change the world to do so from here.”",[],{"_key":25839,"_type":99,"children":25840,"markDefs":25845,"style":799},"bNFcANFpCpnvDkNJDxRj0",[25841],{"_key":25842,"_type":103,"marks":25843,"text":25844},"03e63ecf4003",[],"The opening of the Institute for Computer Science, Artificial Intelligence and Technology (INSAIT) in Sofia is a memorable event. INSAIT has the potential to become the factory for “unicorns” not only in Bulgaria but throughout Eastern Europe, as added by the  EU Commissioner Maria Gabriel who shared the desire to make the institute a platform for future Nobel laureates.",[],{"_key":25847,"_type":99,"children":25848,"markDefs":25853,"style":799},"N03hwTwxxreTAblrFlEm8",[25849],{"_key":25850,"_type":103,"marks":25851,"text":25852},"32668fc8b963",[],"“There are events that change the course of human history and today we have the privilege of being part of such an event. Behind them are always people with knowledge, vision, and energy,” said President Rumen Radev. “The establishment of this institute managed to achieve the impossible for the Bulgarian political reality – to unite the efforts of four successive governments.”",[],{"_key":25855,"_type":99,"children":25856,"markDefs":25861,"style":799},"e3g5LWTA0N49X90_G3P48",[25857],{"_key":25858,"_type":103,"marks":25859,"text":25860},"f2a0e6cc7acd",[],"INSAIT’s mission is to turn Bulgaria into a global destination for research and innovation, as well as a center of a new ecosystem with a direct impact on the country’s development. This is a turning point in efforts to create a high-tech and competitive economy based on high value-added products and intellectual property and to overcome negative trends such as depopulation and the so-called brain drain.",[],{"_key":25863,"_type":99,"children":25864,"markDefs":25869,"style":799},"pB8tflOEXqPIl8BFPStqF",[25865],{"_key":25866,"_type":103,"marks":25867,"text":25868},"d163de90630f",[],"Eastern Europe has an incredible array of talents in computer science and engineering. Jeff Dean, Google AI’s director, shared their desire to help INSAIT become a world-class hub that attracts the best researchers from the region and the world. Google will invest $ 3 million in computing resources, and will also establish special scholarships for women to develop high expertise in computer science.",[],{"_type":17,"current":25757},[25872],{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":25874,"_id":25875,"_rev":25876,"_system":25877,"_type":72,"_updatedAt":25880,"archived":126,"author":161,"category":25881,"date":25314,"description":25885,"image":161,"name":25894,"oldSlug":25895,"orderRank":25896,"reviewer":161,"sections":25897,"seo":161,"slug":26014,"tags":26015},"2026-01-15T15:57:37Z","ac5501b2-63f2-4fef-851d-779b473682f5","3x1HJiv3wwU7cYVoHtQ5rw",{"base":25878},{"id":25875,"rev":25879},"ZfaOePOqVJD5r4KHzTTLgY","2026-01-28T08:46:28Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":25882,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":25884,"uid":54},{"base":25883},{"id":45,"rev":49},{"_type":17,"current":54},[25886],{"_key":25887,"_type":99,"children":25888,"markDefs":25893,"style":107},"9d8f9fd8698d",[25889],{"_key":25890,"_type":103,"marks":25891,"text":25892},"7b46b9358093",[],"Fraud detection is a tough challenge. Fraudulent transactions are extremely infrequent; they account for a small percentage of the total activity within a company.",[],"Evaluating Risk Through AI Models in Order to Detect Financial Fraud","ai-in-financial-fraud","0|1000h4:",[25898],{"_createdAt":25899,"_id":25900,"_key":25901,"_ref":25900,"_rev":25879,"_type":168,"_updatedAt":25899,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":25902,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:50Z","NVQwFD1QaM-Mn_jkv7jgp","4y153Hlgb-9VCZkGlOL8n",[25903,25910,25917,25924,25931,25938,25945,25952,25968,25975,25982,25989,25996,26003],{"_key":25904,"_type":99,"children":25905,"markDefs":25909,"style":799},"L5LykgVJ_qDPkcJEELbEc",[25906],{"_type":103,"marks":25907,"text":25908},[],"Fraud detection is a tough challenge. Fraudulent transactions are extremely infrequent; they account for a small percentage of the total activity within a company. The problem is that without the correct tools and systems in place, a small number of activities can soon develop into severe cash losses. However, AI can be used in financial fraud situation in order to detect it.",[],{"_key":25911,"_type":99,"children":25912,"markDefs":25916,"style":799},"fNpxXd2lN83aQlBIu3HRQ",[25913],{"_type":103,"marks":25914,"text":25915},[],"The emergence of new digital payment channels and technology has created a breeding environment for sophisticated fraud opportunities and bad actors, creating new fraud detection, prevention, and prediction issues. ",[],{"_key":25918,"_type":99,"children":25919,"markDefs":25923,"style":170},"ySNiu6ULDjhIt9GwCadr7",[25920],{"_type":103,"marks":25921,"text":25922},[],"Unfortunately, the fight against financial fraud is an ongoing challenging process.",[],{"_key":25925,"_type":99,"children":25926,"markDefs":25930,"style":799},"OqZU-UyGArADaBtKTw7e9",[25927],{"_type":103,"marks":25928,"text":25929},[],"The reason is the combination of three factors. Firstly, we have numerous transactions in the data structures. The increasing volume of digital transactions and payments puts strain on fraud detection and prevention systems, which must process, analyze, and authorize a greater volume and diversity of payment traffic. ",[],{"_key":25932,"_type":99,"children":25933,"markDefs":25937,"style":799},"OccKm7IIWcNISpt6xthmK",[25934],{"_type":103,"marks":25935,"text":25936},[],"Secondly, the sophistication of “bad actors” is increasing which strongly threatens the business world. Criminals are using sophisticated tools and cutting-edge cyber strategies to bypass older security systems in the ongoing arms race between fraudsters and financial institutions. ",[],{"_key":25939,"_type":99,"children":25940,"markDefs":25944,"style":799},"i1R4zg7RZnyNyPdTN_IPq",[25941],{"_type":103,"marks":25942,"text":25943},[],"Lastly, the identification of verification is difficult. Identity theft is a serious form of cybercrime that affects both individuals and businesses. For instance, real name theft, synthetic theft, and account takeover are the most prevalent types of identity theft. In those cases stolen information is used to open fraudulent new accounts, such as bank checking accounts, credit card accounts, or mobile phone accounts.",[],{"_key":25946,"_type":99,"children":25947,"markDefs":25951,"style":170},"OL6UwQHOqEx5ny--gnV_l",[25948],{"_type":103,"marks":25949,"text":25950},[],"However, the widespread digitalization did not come as an unreversible fraud-feeder environment. The biggest combat against fraud is the 21st century’s game-changer – Artificial Intelligence.",[],{"_key":25953,"_type":99,"children":25954,"markDefs":25965,"style":799},"5HrWdqb8C2zq8MsaFKniG",[25955,25958,25962],{"_type":103,"marks":25956,"text":25957},[],"In fact, businesses have benefited from using AI to detect fraud by enhancing ",{"_type":103,"marks":25959,"text":25961},[25960],"7neJMqpMKz0-VGUhf6AUd","internal security",{"_type":103,"marks":25963,"text":25964},[]," and simplifying corporate procedures. As a result of its enhanced efficiency, AI has emerged as a crucial instrument for preventing financial crimes.",[25966],{"_key":25960,"_type":173,"href":25967},"https://cosmosthrace.com/ai-and-cyber-security/",{"_key":25969,"_type":99,"children":25970,"markDefs":25974,"style":799},"cKjQR39AwOaxKWNcdZ0o9",[25971],{"_type":103,"marks":25972,"text":25973},[],"For example, Artificial Intelligence (AI) may be used to analyze large amounts of data in order to find fraud patterns, which can then be used to detect fraud in real-time. Thus, when fraud is suspected, AI models can be used to either reject or flag transactions for additional investigation. Furthermore, it can grade the likelihood of fraud, allowing investigators to focus their efforts on the most promising cases.",[],{"_key":25976,"_type":99,"children":25977,"markDefs":25981,"style":799},"3JRbRJfcm15lt7u0j6cBY",[25978],{"_type":103,"marks":25979,"text":25980},[],"To be more specific, supervised Machine Learning uses alert reduction algorithms to drastically reduce false positive alerts and alert storms. This approach allows teams to concentrate their efforts on the most important warnings. Users also notice a decrease in the number of legitimate transactions that are incorrectly refused. On the other hand, even when criminal actors adopt new approaches and schemes, AI systems efficiently capture false negatives and minimize the number of fraud cases.",[],{"_key":25983,"_type":99,"children":25984,"markDefs":25988,"style":799},"EmY_qX-dZHgGDQgvUzv7y",[25985],{"_type":103,"marks":25986,"text":25987},[],"As a result of the use of AI, fraud prevention expenditures are being reduced. Financial organizations can benefit from risk scoring and fraud protection systems in a variety of ways. While the major benefit is lower fraud-related monetary damages, these technologies also benefit the bottom line by lowering expenses. Those costs cane be for manual fraud investigations, enhancing customer happiness, and lowering customer attrition.",[],{"_key":25990,"_type":99,"children":25991,"markDefs":25995,"style":170},"2NJCnRIKr2tN9XrYA3Ijz",[25992],{"_type":103,"marks":25993,"text":25994},[],"Takeaways",[],{"_key":25997,"_type":99,"children":25998,"markDefs":26002,"style":799},"b_wCnIjJgJ9axjMaxKabI",[25999],{"_type":103,"marks":26000,"text":26001},[],"Combining supervised and unsupervised machine learning as part of a bigger Artificial Intelligence (AI) fraud detection strategy can help digital businesses discover automated and more complex fraud attempts faster and more accurately. The digital age is, undoubtedly, an open space for innovations, but businesses should not underestimate the risks and challenges. In a nutshell, companies should extract digitalization’s benefits learn how to control it to their advantage. ",[],{"_key":26004,"_type":99,"children":26005,"markDefs":26012,"style":799},"IjJLGSA8kyO0Hcat2aJUk",[26006,26009],{"_type":103,"marks":26007,"text":20869},[26008],"1HE5xBU-GmaOOdV8jHni1",{"_type":103,"marks":26010,"text":26011},[]," if you want to learn more on the possibilities of artificial intelligence!",[26013],{"_key":26008,"_type":173,"href":19536},{"_type":17,"current":25895},[26016,26017,26020],{"_createdAt":24092,"_id":24093,"_rev":24094,"_type":8636,"_updatedAt":24095,"name":24096,"orderRank":16653,"uid":24097},{"_createdAt":21691,"_id":21692,"_rev":21693,"_system":26018,"_type":8636,"_updatedAt":21697,"name":21698,"orderRank":13162,"uid":21699},{"base":26019},{"id":21692,"rev":21696},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":26022,"_id":26023,"_rev":26024,"_system":26025,"_type":72,"_updatedAt":26028,"archived":126,"author":161,"category":26029,"date":26033,"description":26034,"image":161,"name":26043,"oldSlug":26044,"orderRank":26045,"reviewer":161,"sections":26046,"seo":161,"slug":26180,"tags":26181},"2026-01-15T22:04:00Z","800b2fa0-03b5-4651-a994-2e7b343cc409","YkA36qTDOerM1fSJc31L3x",{"base":26026},{"id":26023,"rev":26027},"ZfaOePOqVJD5r4KHzTWzVk","2026-01-26T10:04:45Z",{"_createdAt":56,"_id":57,"_rev":58,"_system":26030,"_type":12,"_updatedAt":62,"name":63,"orderRank":64,"slug":26032,"uid":66},{"base":26031},{"id":57,"rev":61},{"_type":17,"current":66},"2022-12-08",[26035],{"_key":26036,"_type":99,"children":26037,"markDefs":26042,"style":107},"7d1145ed7dcb",[26038],{"_key":26039,"_type":103,"marks":26040,"text":26041},"0a2ff9576384",[],"Dani Matev is a fourth-year student at the Technical University in Sofia, majoring in Computer and Software Engineering. Although he was born and raised in",[],"From a Student to a Key Member of the Team of Cosmos Thrace","from-a-student-to-a-data-analytics-career-cosmos-thrace","0|1000vs:",[26047],{"_createdAt":26048,"_id":26049,"_key":26050,"_ref":26049,"_rev":26027,"_type":168,"_updatedAt":26048,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":26051,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:45:22Z","bOJMIbJfmlO2MeJaAT6oB","8klpzSWWYIurGWudAIlax",[26052,26059,26066,26073,26080,26087,26094,26101,26108,26115,26122,26129,26136,26143,26150,26157,26164,26171],{"_key":26053,"_type":99,"children":26054,"markDefs":26058,"style":799},"dN00HoDiaEAsAycZkr1Kg",[26055],{"_type":103,"marks":26056,"text":26057},[],"Dani Matev is a fourth-year student at the Technical University in Sofia, majoring in Computer and Software Engineering. Although he was born and raised in Varna, the sea capital of Bulgaria, his passion for data analysis and Artificial Intelligence inspired him to move to Sofia where is currently pursuing a data analytics career. ",[],{"_key":26060,"_type":99,"children":26061,"markDefs":26065,"style":170},"D8J9Sbls_CKmbl4gxKJhI",[26062],{"_type":103,"marks":26063,"text":26064},[],"The Beginning of a Collaboration",[],{"_key":26067,"_type":99,"children":26068,"markDefs":26072,"style":799},"vhV71K426XXo0HzRX6byL",[26069],{"_type":103,"marks":26070,"text":26071},[],"Dani has been at Cosmos Thrace for a year now and the knowledge he gained from his first-hand experience at the company has strengthened his interest in process automatization and computer science. He is currently working as a data scientist and AI specialist at Cosmos Thrace in order to pursue a data analytics career.",[],{"_key":26074,"_type":99,"children":26075,"markDefs":26079,"style":799},"o5HpKzSW00upKScF7C4OO",[26076],{"_type":103,"marks":26077,"text":26078},[],"He recalls how a close friend of his, who also worked at Cosmos Thrace, introduced him to the culture of the company and its vision. His interview with the CEO Viktor Elefterov created an instant rapport as they both found a match in their capabilities and beliefs. ",[],{"_key":26081,"_type":99,"children":26082,"markDefs":26086,"style":170},"KPIXJs43lkmdMcw4crSzV",[26083],{"_type":103,"marks":26084,"text":26085},[],"Where does your Inspiration Come From?",[],{"_key":26088,"_type":99,"children":26089,"markDefs":26093,"style":799},"XS2DOVeo1HQt73LnNyl2E",[26090],{"_type":103,"marks":26091,"text":26092},[],"Dani has recently started working on two data science and AI projects. One of them is the preventative measure for machinery breakdowns. The project focuses on building a system of predictive maintenance that predicts the time at which a certain machine might fail in order to prevent this from happening. ",[],{"_key":26095,"_type":99,"children":26096,"markDefs":26100,"style":799},"k3kAgilODb6x0Mpgb891x",[26097],{"_type":103,"marks":26098,"text":26099},[],"Another interesting project Dani is involved in is a bank transaction classification system where machine learning assigns a category to different bank transactions, for example, food, loan payments, etc. The projects have been engaging so far, helping Dani to apply his theoretical knowledge in practice.",[],{"_key":26102,"_type":99,"children":26103,"markDefs":26107,"style":170},"epbE--4jWpd1ZiIkgtmM3",[26104],{"_type":103,"marks":26105,"text":26106},[],"Opportunity for Growth",[],{"_key":26109,"_type":99,"children":26110,"markDefs":26114,"style":799},"jzluqMSlyZO3M8qO65Lec",[26111],{"_type":103,"marks":26112,"text":26113},[],"Dani highly appreciates the opportunity for growth and autonomy provided at Cosmos Thrace. ",[],{"_key":26116,"_type":99,"children":26117,"markDefs":26121,"style":799},"KQl8vneJrOu1M_iM_9NGg",[26118],{"_type":103,"marks":26119,"text":26120},[],"“There is no judgmental culture, so if you want to improve, you can. If you want to improve a certain process, even if there is a risk of failure you will be given the chance to grow. This way you can improve both yourself and the company,” shares Dani.",[],{"_key":26123,"_type":99,"children":26124,"markDefs":26128,"style":170},"Epb39kfkTiuuZ3_w0Q87i",[26125],{"_type":103,"marks":26126,"text":26127},[],"Academic, Professional and Personal Life",[],{"_key":26130,"_type":99,"children":26131,"markDefs":26135,"style":799},"w7F0YdCF3hUT1s6USlT41",[26132],{"_type":103,"marks":26133,"text":26134},[],"Being a student at the Technical University in Sofia and pursuing a data analytics career takes up a lot of Dani’s time. Currently, he is spending a lot of time improving himself as a person. He likes reading self-help books about emotional intelligence and learning more about how the human brain works. In other words – learn how your inside world operates to master the art of building an operational artificial one.",[],{"_key":26137,"_type":99,"children":26138,"markDefs":26142,"style":799},"SDXqqdlpsUZ8-aqtNwHP1",[26139],{"_type":103,"marks":26140,"text":26141},[],"He has also been spotted scribbling on the big whiteboards in the office, where you can find drawings from his favorite movies and illustrations of many internal jokes between the teammates at Cosmos Thrace. Dani believes this is another way in which the company encourages freedom of expression and development.",[],{"_key":26144,"_type":99,"children":26145,"markDefs":26149,"style":170},"8h5oKyvermdPDvJ5Y12jh",[26146],{"_type":103,"marks":26147,"text":26148},[],"What Does the Future Hold?",[],{"_key":26151,"_type":99,"children":26152,"markDefs":26156,"style":799},"F2wkRY7182i7yUs0eBIBq",[26153],{"_type":103,"marks":26154,"text":26155},[],"Dani is striving to further advance his tech team leadership and management skills. ",[],{"_key":26158,"_type":99,"children":26159,"markDefs":26163,"style":799},"e0ubKLmnG3tz8ewBOwFEi",[26160],{"_type":103,"marks":26161,"text":26162},[],"“I want to improve my management skills and I believe Cosmos Thrace is giving really good opportunities to people like me. I strongly support this as a part of the culture of Cosmos Thrace – to encourage innovation and to allow proactive people,” claims Dani.",[],{"_key":26165,"_type":99,"children":26166,"markDefs":26170,"style":799},"Rt8w1Cj5GU-ERKAesl57v",[26167],{"_type":103,"marks":26168,"text":26169},[],"He has already managed a team project and has been a scrum master of another. Even though he admits he does not have a lot of experience in that area, the company has given him the chance to find what he enjoys doing, namely being a project manager.",[],{"_key":26172,"_type":99,"children":26173,"markDefs":26178,"style":799},"bywMCifsh_ikRK7Sl1MEG",[26174],{"_type":103,"marks":26175,"text":26177},[26176],"5r-Fsvy01xTy2MOUbnS3d","Check out our open positions to learn more!",[26179],{"_key":26176,"_type":173,"href":20182},{"_type":17,"current":26044},[26182],{"_createdAt":22463,"_id":22464,"_rev":22465,"_type":8636,"_updatedAt":22466,"name":22467,"orderRank":22468,"uid":22469},{"_createdAt":26184,"_id":26185,"_rev":26186,"_system":26187,"_type":72,"_updatedAt":26190,"archived":126,"author":161,"category":26191,"date":26195,"description":26196,"image":161,"name":26205,"oldSlug":26206,"orderRank":26207,"reviewer":161,"sections":26208,"seo":161,"slug":26337,"tags":26338},"2026-01-15T15:58:35Z","025edb58-b002-4104-adbd-94900385f784","ir9xdmjsDvNqVMLz9XoRM9",{"base":26188},{"id":26185,"rev":26189},"ZfaOePOqVJD5r4KHzTTMLP","2026-01-28T08:51:12Z",{"_createdAt":32,"_id":33,"_rev":34,"_system":26192,"_type":12,"_updatedAt":38,"name":39,"orderRank":40,"slug":26194,"uid":42},{"base":26193},{"id":33,"rev":37},{"_type":17,"current":42},"2022-12-07",[26197],{"_key":26198,"_type":99,"children":26199,"markDefs":26204,"style":107},"ce1e2a5dee93",[26200],{"_key":26201,"_type":103,"marks":26202,"text":26203},"6317b7dd9a52",[],"One of the most challenging and complex aspects of any digital transformation is data migration. In the last decade, the importance of data in business",[],"What role does Data Migration play in the Digital Transformation journey?","what-role-does-data-migration-play-in-the-digital-transformation-journey","0|1000i0:",[26209],{"_createdAt":26210,"_id":26211,"_key":26212,"_ref":26211,"_rev":26189,"_type":168,"_updatedAt":26210,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":26213,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:54Z","Qt3Qjgw-NJ_8Cps4vP9fc","bhZHp_uVpzhFvQ_98th-4",[26214,26230,26237,26244,26260,26267,26274,26281,26288,26295,26302,26309,26316],{"_key":26215,"_type":99,"children":26216,"markDefs":26227,"style":799},"nyCwg7ASWa_6FrmLpxcLv",[26217,26220,26224],{"_type":103,"marks":26218,"text":26219},[],"One of the most challenging and complex aspects of any ",{"_type":103,"marks":26221,"text":26223},[26222],"OK2FujLMczF9Z0j80KwtP","digital transformation",{"_type":103,"marks":26225,"text":26226},[]," is data migration. In the last decade, the importance of data in business has shifted considerably. It has evolved from a departmental role to a critical facilitator of digital transformation. The core of modern enterprises of all sizes is data centricity. Building a genuinely data-driven business require large-scale data transfer and modernization. However, this data transformation process entails much more than simply moving the data estate to the cloud.",[26228],{"_key":26222,"_type":173,"href":26229},"https://cosmosthrace.com/should-you-consider-digital-transformation-as-a-way-to-gain-competitive-advantage/",{"_key":26231,"_type":99,"children":26232,"markDefs":26236,"style":170},"-ojpCbz1L6XHlpGwxIDO3",[26233],{"_type":103,"marks":26234,"text":26235},[],"Therefore, data migration should move up on the companies’ lists of project priorities.",[],{"_key":26238,"_type":99,"children":26239,"markDefs":26243,"style":799},"9ziY1poqpgm_o5a2l-VTf",[26240],{"_type":103,"marks":26241,"text":26242},[],"However, most businesses overlook the need for data migration work as a prerequisite for a successful ERP implementation/digital transformation. Many businesses are unaware of the numerous difficulties or stages that are part of the digital transformation journey. It is an iterative process to migrate data. Some people wrongly believe that data can be transferred using (auto-magical) “lift and shift” technologies, or that someone else on the team will design and conduct the heavy lifting.",[],{"_key":26245,"_type":99,"children":26246,"markDefs":26257,"style":799},"EOQ-93MCb1Deu4A7eaWLs",[26247,26250,26254],{"_type":103,"marks":26248,"text":26249},[],"Data is frequently added too late in the project cycle when data readiness is not a well-planned pillar of the project. This results in the early discovery of system problems. Project delays and costly design/build/test rework cycles can cause late modifications to the new system. A possible impact is “dirty data.” When you fail to plan and implement data adequately in advance usually “trash in, garbage out” happens. B",{"_type":103,"marks":26251,"text":26253},[26252],"3QSFt3tLjaL1Wf6wnEIx1","usiness intelligence",{"_type":103,"marks":26255,"text":26256},[],", data analytics, the internet of things (IoT), and other large-scale IT efforts have potential. However, if a company has corrupted, inconsistent, or wrong data, these technological tools are useless.",[26258],{"_key":26252,"_type":173,"href":26259},"https://cosmosthrace.com/what-is-business-intelligence/",{"_key":26261,"_type":99,"children":26262,"markDefs":26266,"style":170},"LcgM6DpCG4wQkK80PKOy_",[26263],{"_type":103,"marks":26264,"text":26265},[],"Here comes another term in data transformation, namely “data cleansing.”",[],{"_key":26268,"_type":99,"children":26269,"markDefs":26273,"style":799},"LIYNoEhyA0bFA4IDyoDH8",[26270],{"_type":103,"marks":26271,"text":26272},[],"Data cleaning necessitates more extensive pre-work or may require external validation. Therefore, it is usually done before the actual data migration. Usually, skipping data cleansing phase is uncommon, even though it should start before software selection. ",[],{"_key":26275,"_type":99,"children":26276,"markDefs":26280,"style":799},"4ZqcXiVlX9pIS23MWy-qJ",[26277],{"_type":103,"marks":26278,"text":26279},[],"Data transformation is a systematic, programmed method for transforming large amounts of data according to established business and technical standards. The project team will be able to incorporate significant volumes of changed live data into the newly developed system for effective/realistic testing. Moreover, transformation is meant to be done iteratively and frequently. This entails not only comprehending the technical elements but also obtaining the necessary authorization for the mapping as to who has access to what data.",[],{"_key":26282,"_type":99,"children":26283,"markDefs":26287,"style":170},"P1LLTl7w9oIuTIPO9x0gF",[26284],{"_type":103,"marks":26285,"text":26286},[],"Even when digital transformation is now an essence in the business world, some companies still put off confirming their data until user acceptability testing.",[],{"_key":26289,"_type":99,"children":26290,"markDefs":26294,"style":799},"my8IFDL5GOKIL7OvaRKeC",[26291],{"_type":103,"marks":26292,"text":26293},[],"The main reason here is the lack of a “data readiness track” to ensure that any meaningful data is available for testing. A significant drawback of data testing late in the journey is that is unlikely to complete it before going live. In addition, downstream systems, reports, and analytics will not be executed or tested with master and transactional data.",[],{"_key":26296,"_type":99,"children":26297,"markDefs":26301,"style":799},"TNMClT6W10LP_xb_ZHfmE",[26298],{"_type":103,"marks":26299,"text":26300},[],"Since the system integrator is usually primarily responsible for the main ERP system, it cannot guarantee that downstream systems and reporting can correctly process the outputs. This can lead to an unpleasant surprise when an executive realises the poor state of data in their new dashboards. Data readiness preparation might help companies avoid unpleasant surprises after project’s completion.",[],{"_key":26303,"_type":99,"children":26304,"markDefs":26308,"style":170},"nT_K4dYxbBix5H3YICfxo",[26305],{"_type":103,"marks":26306,"text":26307},[],"And finally, what happens with the privacy and security concerns around data migration?",[],{"_key":26310,"_type":99,"children":26311,"markDefs":26315,"style":799},"aeYf3PCmNGhTCe6lPLud2",[26312],{"_type":103,"marks":26313,"text":26314},[],"Data migration, data privacy, and data security all need data mapping and cataloging efforts. A company must first understand what data it has and how it travels and is utilized within the business to safeguard it. If teams adopt data privacy and security in time, the data transfer team can benefit from it. When a company is considering a data privacy or security program (highly recommended for any size company), they should look for ways to combine part of their work with data migration efforts. Furthermore, a migration team can work with (and understand) the relational benefits of doing so – a company can save a lot of time, resources, and expenses.",[],{"_key":26317,"_type":99,"children":26318,"markDefs":26334,"style":799},"ION7cqSckbucTwH87ftKp",[26319,26322,26326,26329,26332],{"_type":103,"marks":26320,"text":26321},[],"Do you need data migration service in order to complete your digital transformation journey? Do not hesitate to ",{"_type":103,"marks":26323,"text":26325},[26324],"aTParPOxRrCeD9lw8qdsT","book a free call",{"_type":103,"marks":26327,"text":26328},[]," or look at our full portfolio of ",{"_type":103,"marks":26330,"text":19370},[26331],"xWG-R_7Yp89cPujXYwK94",{"_type":103,"marks":26333,"text":20704},[],[26335,26336],{"_key":26324,"_type":173,"href":19536},{"_key":26331,"_type":173,"href":19377},{"_type":17,"current":26206},[26339,26340],{"_createdAt":22913,"_id":22914,"_rev":22915,"_type":8636,"_updatedAt":22916,"name":22917,"orderRank":18786,"uid":22918},{"_createdAt":10726,"_id":10727,"_rev":10728,"_type":8636,"_updatedAt":10729,"name":14,"orderRank":10730,"uid":18},{"_createdAt":26342,"_id":26343,"_rev":26344,"_system":26345,"_type":72,"_updatedAt":26348,"archived":126,"author":161,"category":26349,"date":26195,"description":26353,"image":161,"name":26362,"oldSlug":26363,"orderRank":26364,"reviewer":161,"sections":26365,"seo":161,"slug":26495,"tags":26496},"2026-01-15T16:03:02Z","1951fcc5-7272-44c6-b857-33171dead3fa","3x1HJiv3wwU7cYVoHtQyse",{"base":26346},{"id":26343,"rev":26347},"2oGVswEwQBfyYUvi7k5KFt","2026-01-28T08:47:22Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":26350,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":26352,"uid":54},{"base":26351},{"id":45,"rev":49},{"_type":17,"current":54},[26354],{"_key":26355,"_type":99,"children":26356,"markDefs":26361,"style":107},"46a1620a5a25",[26357],{"_key":26358,"_type":103,"marks":26359,"text":26360},"0c70d7a660c0",[],"One of the most important variables in predicting long-term business growth is sales forecasting. It largely occupies managers’ time and attention. Unfortunately, sales forecasting has",[],"AI and E-commerce: Forecasting Sales for Better Planning","ai-and-e-commerce-forecasting-sales-for-better-planning","0|1000ko:",[26366],{"_createdAt":26367,"_id":26368,"_key":26369,"_ref":26368,"_rev":26347,"_type":168,"_updatedAt":26367,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":26370,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:37:29Z","3Ejnv9_LgmHhePgJ1LgNY","Ke2RPkcYYFE6OLolOPZbv",[26371,26378,26385,26392,26399,26415,26422,26429,26436,26443,26450,26457,26464,26471,26478],{"_key":26372,"_type":99,"children":26373,"markDefs":26377,"style":799},"m5HXnQ9gILlbAogALDddE",[26374],{"_type":103,"marks":26375,"text":26376},[],"One of the most important variables in predicting long-term business growth is sales forecasting. It largely occupies managers’ time and attention. Unfortunately, sales forecasting has proven as an imprecise art, despite the enormous time spent on researching and analyzing different data. Here comes the role of AI in E-commerce and its numerous possibilities. Read along to learn how to forecast sales through Artificial Intelligence technology.",[],{"_key":26379,"_type":99,"children":26380,"markDefs":26384,"style":170},"7tG0B3ZDsLFASBOIMGyOd",[26381],{"_type":103,"marks":26382,"text":26383},[],"How is sales forecasting currently done?",[],{"_key":26386,"_type":99,"children":26387,"markDefs":26391,"style":799},"VsylbBCv80wYeZbob8R_S",[26388],{"_type":103,"marks":26389,"text":26390},[],"While conventional sales forecasting methods range from in-depth historical investigations to gut instincts, weighted pipeline forecasting is the most widely utilized method in today’s business world. In it, every sales opportunity in the pipeline gets a percentage likelihood of closing a deal.  Then, it is multiplied by the revenue value associated with the opportunity. The sales forecast is estimated by the sum of all revenue values.",[],{"_key":26393,"_type":99,"children":26394,"markDefs":26398,"style":170},"5aMRh_jLNY-wj2u32GM9k",[26395],{"_type":103,"marks":26396,"text":26397},[],"So, how can sales forecasting be enhanced for better planning?",[],{"_key":26400,"_type":99,"children":26401,"markDefs":26412,"style":799},"XtBjxdEUgvJfsRnx4Zkn0",[26402,26405,26409],{"_type":103,"marks":26403,"text":26404},[],"The way organizations are using artificial intelligence (AI), machine learning (ML), and predictive analytics, revolutionizes how the world perceives predicting sales. Only a quarter of businesses, according to ",{"_type":103,"marks":26406,"text":26408},[26407],"Zm0_NECKPRB7jW-Z5Ktuh","Salesforce",{"_type":103,"marks":26410,"text":26411},[],", use predictive analytics. Moreover, of those who use it, 86 percent of individuals, have already noticed a beneficial result. Predictive analytics may be integrated into the CRM to help sales representatives, partners, and managers produce more accurate sales projections. Through that approach, they can gain actionable insights. ",[26413],{"_key":26407,"_type":173,"href":26414},"https://www.salesforce.com/blog/what-is-predictive-analytics/?zd_source=mta&zd_campaign=14972&zd_term=geoffbirnes&zd_source=mta&zd_campaign=14972&zd_term=geoffbirnes",{"_key":26416,"_type":99,"children":26417,"markDefs":26421,"style":170},"Bd2cB59HWEVbmQpRuwufx",[26418],{"_type":103,"marks":26419,"text":26420},[],"How does AI in E-commerce contribute to the welfare of businesses?",[],{"_key":26423,"_type":99,"children":26424,"markDefs":26428,"style":799},"X7Ef2LAN870VsHedxx-jd",[26425],{"_type":103,"marks":26426,"text":26427},[],"Business is currently driven by huge amounts of data. Companies must have the right skills and tools to translate data into actionable insights to use it effectively. This is the foundation of a data-driven experience or in other words “intelligent experience” where system users are supplied with actionable information in the context of their workflow. A corporation utilizing a typical CRM, for example, can view pipeline and opportunity data as well as expected sales figures. ",[],{"_key":26430,"_type":99,"children":26431,"markDefs":26435,"style":799},"xTe1HCT3FHYcqJh7K9cpu",[26432],{"_type":103,"marks":26433,"text":26434},[],"In contrast, a corporation that uses intelligent forecasting (AI) gets all of the same data with some additional assumptions and suggestions in a usable format. Firstly, the intelligent forecast predictions will look at prior opportunities, hits, misses, win rates, and other factors. Then they will generate a recommended forecast that can be compared to field inputs. The most important differentiation when it comes to intelligent forecasting is the capacity to improve accuracy and confidence, as well as provide insights and actions to boost sales volumes.",[],{"_key":26437,"_type":99,"children":26438,"markDefs":26442,"style":170},"Trw0mrTzR_PS9mfdABtc9",[26439],{"_type":103,"marks":26440,"text":26441},[],"How to approach intelligence experience in forecasting?",[],{"_key":26444,"_type":99,"children":26445,"markDefs":26449,"style":799},"xRbHItVPJXRYMXmq1jyHY",[26446],{"_type":103,"marks":26447,"text":26448},[],"A multi-tier channel sales organization, for example, will have different requirements than a direct sales organization. To estimate each income channel, multiple data sets and algorithms will be necessary. Propensity-based predictions for direct sales and run rate predictions for both channel sales and aggregate forecast rollups are the two most frequent prediction methodologies. Run rate models look at aggregate sales volumes across segments of the business, whereas propensity-based models look at individual opportunities and score them (i.e., channel, geography, product, etc.). The insights are pooled across both techniques and integrated into user processes within the CRM once they’ve been applied.",[],{"_key":26451,"_type":99,"children":26452,"markDefs":26456,"style":170},"aUaKyYyC6ihDpSL5i1GOK",[26453],{"_type":103,"marks":26454,"text":26455},[],"Intelligent forecasting in e-commerce.",[],{"_key":26458,"_type":99,"children":26459,"markDefs":26463,"style":799},"3D1E-mA8sro_G77U4ecRv",[26460],{"_type":103,"marks":26461,"text":26462},[],"On the one hand, when used in areas like fraud detection, picture categorization, price optimization, and consumer segmentation, it can improve corporate efficiency. However, it has a lot of potential for improving the user experience on these platforms by making algorithm-driven product suggestions and providing content personalization, virtual assistants, and better search capabilities. All of this will help businesses stand out from the crowd, allowing them to better position themselves against the competition.",[],{"_key":26465,"_type":99,"children":26466,"markDefs":26470,"style":799},"1Z-UcH4VpDaQsIhgP9vs4",[26467],{"_type":103,"marks":26468,"text":26469},[],"Customers are beginning to expect a personalized experience while transacting; therefore, understanding each consumer individually enables this. Companies accomplish this through machine learning-driven technologies that enable real-time content updates depending on user behaviour. Those algorithms predict the shopper’s next move in the online store and expedite the buying process, putting the merchant ahead of the game. Furthermore, chatbots or virtual assistants not only increase consumer interactions but may also give support and create promotions depending on user preferences.",[],{"_key":26472,"_type":99,"children":26473,"markDefs":26477,"style":799},"pETEsKgb_bw6XpkQ5qDS6",[26474],{"_type":103,"marks":26475,"text":26476},[],"Intelligent forecasting is now more accessible than ever before. Companies are merging data, analytics, and artificial intelligence (AI) to increase sales predictability and performance in e-commerce. Making the most out of it benefits companies to get a competitive advantage and utilize their connection with their customers.",[],{"_key":26479,"_type":99,"children":26480,"markDefs":26492,"style":799},"1EzUeBKWLK17U_-rdxg58",[26481,26484,26487,26490],{"_type":103,"marks":26482,"text":20869},[26483],"q52aXjrULaidJ8kjOu82h",{"_type":103,"marks":26485,"text":26486},[]," to improve your E-commerce business and gain a competitive advantage! You can also check our full portfolio of ",{"_type":103,"marks":26488,"text":19370},[26489],"9w45J8djWGHell_HIkzQn",{"_type":103,"marks":26491,"text":20704},[],[26493,26494],{"_key":26483,"_type":173,"href":19536},{"_key":26489,"_type":173,"href":19377},{"_type":17,"current":26363},[26497,26500,26501,26502],{"_createdAt":21691,"_id":21692,"_rev":21693,"_system":26498,"_type":8636,"_updatedAt":21697,"name":21698,"orderRank":13162,"uid":21699},{"base":26499},{"id":21692,"rev":21696},{"_createdAt":21701,"_id":21702,"_rev":21703,"_type":8636,"_updatedAt":21704,"name":21705,"orderRank":12869,"uid":21706},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":12143,"_id":12144,"_rev":12145,"_type":8636,"_updatedAt":12146,"name":12147,"orderRank":12148,"uid":12149},{"_createdAt":26504,"_id":26505,"_rev":26506,"_system":26507,"_type":72,"_updatedAt":26510,"archived":126,"author":161,"category":26511,"date":26195,"description":26515,"image":161,"name":26524,"oldSlug":26525,"orderRank":26526,"reviewer":161,"sections":26527,"seo":161,"slug":26647,"tags":26648},"2026-01-15T16:11:24Z","3293d0c7-875b-46d9-844e-fc06eb76423a","7hw4Cb1llohacCi9MHyJL1",{"base":26508},{"id":26505,"rev":26509},"2oGVswEwQBfyYUvi7k5zai","2026-01-28T08:47:46Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":26512,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":26514,"uid":54},{"base":26513},{"id":45,"rev":49},{"_type":17,"current":54},[26516],{"_key":26517,"_type":99,"children":26518,"markDefs":26523,"style":107},"a74e83e56c02",[26519],{"_key":26520,"_type":103,"marks":26521,"text":26522},"34165ae2302e",[],"A virtual representation, simulation, or mapping of a real entity, such as a process, person, item, system, or any other abstraction, is known as a",[],"Digital Twins: What to expect and look out for?","what-are-digital-twins","0|1000oo:",[26528],{"_createdAt":26529,"_id":26530,"_key":26531,"_ref":26530,"_rev":26509,"_type":168,"_updatedAt":26529,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":26532,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:33Z","OADmqqlUz7flfmuOZYb1m","Ui_2tVw-b0B6Ms984x2Sn",[26533,26540,26547,26554,26561,26568,26575,26582,26589,26596,26603,26610,26617,26623,26630],{"_key":26534,"_type":99,"children":26535,"markDefs":26539,"style":799},"JtNIHfxL0lFeyBZVxiSrr",[26536],{"_type":103,"marks":26537,"text":26538},[],"A virtual representation, simulation, or mapping of a real entity, such as a process, person, item, system, or any other abstraction, is known as a Digital Twin. While the concept is not new, IoT proliferation, hyper-automation, and real-time data flow are increasing digital twin technology’s significance. Digital twins are a new type of business software that leverages the Internet of Things (IoT) to track, analyze, and manage business operations.",[],{"_key":26541,"_type":99,"children":26542,"markDefs":26546,"style":170},"rs9PwisGQKRoYfmJb2kus",[26543],{"_type":103,"marks":26544,"text":26545},[],"There are several varieties of digital twins that are ideal for the jobs that must be completed during the manufacturing process.",[],{"_key":26548,"_type":99,"children":26549,"markDefs":26553,"style":799},"JziYlRyzrOz-qLiQlLobx",[26550],{"_type":103,"marks":26551,"text":26552},[],"With rudimentary filtering, a status twin can provide real-time monitoring and visualization possibilities. The users are left to interpret the outcomes in this case. Basic analytics can be used by an operational twin to conditionally monitor a process. It can make suggestions and do automatic actions. Organizations can use predictive twins to anticipate the quality of output or even an equipment breakdown. Thus, this so-called sort of twin can help you optimize your maintenance cycles and strike a balance between corrective and preventative maintenance. A simulation twin may simulate several scenarios and preview various sorts of outcomes by replicating a system’s various operations.",[],{"_key":26555,"_type":99,"children":26556,"markDefs":26560,"style":170},"KzWUaOPf3ntvEUoIgyUzN",[26557],{"_type":103,"marks":26558,"text":26559},[],"Undoubtedly, digital twins are here for good. However, what has the business world already exploited from them?",[],{"_key":26562,"_type":99,"children":26563,"markDefs":26567,"style":799},"6nZ2OJrWAy-3H-sj5ShKZ",[26564],{"_type":103,"marks":26565,"text":26566},[],"Digital twins provide a real-time view of what’s going on with physical assets, which can significantly reduce maintenance costs. Companies utilize digital twin technology for a variety of reasons, including improving existing operations, training staff, and testing new goods or procedures before releasing them into the real world, where fixing any flaws becomes more expensive and harder.",[],{"_key":26569,"_type":99,"children":26570,"markDefs":26574,"style":799},"QimbbjxD_WbGvDnLqbAnE",[26571],{"_type":103,"marks":26572,"text":26573},[],"Firstly, a striking benefit of digital twins is the possibility of a test before manufacturing. Before investing in the construction or deployment of systems, equipment concepts, or service models, companies can employ digital twins to design and test them. If a model proves to be successful, it may be connected to the physical construct for real-time monitoring.",[],{"_key":26576,"_type":99,"children":26577,"markDefs":26581,"style":799},"56lYtoSa4BzlgaWLnZpsa",[26578],{"_type":103,"marks":26579,"text":26580},[],"Moreover, using digital twins to monitor everyday operations and simplify manufacturing lowers excessive wear and tear on machinery while also alerting business managers to possible cost-cutting opportunities. Improved total productivity and efficiency help organizations to maintain a competitive edge through faster maintenance and repair.",[],{"_key":26583,"_type":99,"children":26584,"markDefs":26588,"style":799},"DZv_67Lp1OFkJaZ_O4WyX",[26585],{"_type":103,"marks":26586,"text":26587},[],"Lastly, customer-facing applications, such as remote troubleshooting, are also available with digital twins. Instead of depending on default procedures, personnel may do diagnostic testing from anywhere and take consumers through the appropriate processes for repair by using virtual models. The data acquired during these sessions is extremely useful for future product planning and development.",[],{"_key":26590,"_type":99,"children":26591,"markDefs":26595,"style":170},"4sgjfzEdJytX6IrfFUhaj",[26592],{"_type":103,"marks":26593,"text":26594},[],"Despite the advantages, there are also drawbacks to using digital twins.",[],{"_key":26597,"_type":99,"children":26598,"markDefs":26602,"style":799},"YPwCkE2r1RsdrIZh14HES",[26599],{"_type":103,"marks":26600,"text":26601},[],"For everyone engaged, the technology provides a new range of applications. As a result, there are no industry-ready products available for deployment off the shelf. However, each sector needs customized digital twin solutions that are tailored to their specific demands. As a result, a slew of digital twin companies is offering packaged offers alongside their headline goods and services to meet those demands.",[],{"_key":26604,"_type":99,"children":26605,"markDefs":26609,"style":799},"MfLiYAfYMmVQZkeOh77-2",[26606],{"_type":103,"marks":26607,"text":26608},[],"Here comes the infrastructural problem. The infrastructure required to deploy the digital twin concept is not available to all businesses. Many firms have yet to be exposed to the technology because it is still relatively new. Real-time data may be used to uncover the true value of digital twins. This means that this technology is largely reliant on Internet of Things (IoT) devices and a system of networked equipment, objects, or people with unique IDs and a continuous data flow between them. It is difficult to apply this technology in firms that have not developed this infrastructure.",[],{"_key":26611,"_type":99,"children":26612,"markDefs":26616,"style":799},"ISUiacT8H8Q8Vchuu-ZgD",[26613],{"_type":103,"marks":26614,"text":26615},[],"Therefore, the faster a new form of technology spreads, the less attention it receives in terms of security. The gathering and use of huge data volumes come from a variety of endpoints. Any of them may be a source of failure. Every time a new connection is established, and more data is sent between devices and the cloud, the danger of a security breach grows. As a result, companies contemplating digital twin technology should always be cautious. Furthermore, they should not proceed without first analyzing and upgrading their present security policies.",[],{"_key":26618,"_type":99,"children":26619,"markDefs":26622,"style":170},"qa_e5wi1lvWzh2mjWn8Rm",[26620],{"_type":103,"marks":26621,"text":4733},[],[],{"_key":26624,"_type":99,"children":26625,"markDefs":26629,"style":799},"rHUctQ16Cb64NY7Pr2kaw",[26626],{"_type":103,"marks":26627,"text":26628},[],"The implementation of digital twins usually is a crossroad of data science and business process management. Before commencing on this digital twin adoption journey, an organization should analyze its data maturity and process measurement capabilities. A business should assess its needs to adopt the proper type of digital twin and harvest the benefits of its implementation. Nevertheless, Digital twin deployment might cost a lot of money depending on how complicated the project is. Furthermore, adopting digital twins technology on one process usually impacts other processes, meaning that it needs extensive planning and collaboration. Therefore, companies should look out for the challenges that come along this automation journey.",[],{"_key":26631,"_type":99,"children":26632,"markDefs":26644,"style":799},"h9Cyp4a8fFvC-nrbnBWLB",[26633,26636,26639,26642],{"_type":103,"marks":26634,"text":20869},[26635],"NbSHIFEoM_70t0hl3NkW-",{"_type":103,"marks":26637,"text":26638},[]," if you want to learn more about digital twins or look at our full portfolio of ",{"_type":103,"marks":26640,"text":19370},[26641],"EEFSvNdZgE7EjcpAFxkul",{"_type":103,"marks":26643,"text":20704},[],[26645,26646],{"_key":26635,"_type":173,"href":19536},{"_key":26641,"_type":173,"href":19377},{"_type":17,"current":26525},[26649,26650],{"_createdAt":20710,"_id":20711,"_rev":20712,"_type":8636,"_updatedAt":20713,"name":20714,"orderRank":15218,"uid":20715},{"_createdAt":22144,"_id":22145,"_rev":22146,"_type":8636,"_updatedAt":22147,"name":22148,"orderRank":15683,"uid":22149},{"_createdAt":26652,"_id":26653,"_rev":26654,"_system":26655,"_type":72,"_updatedAt":26658,"archived":126,"author":161,"category":26659,"date":26195,"description":26663,"image":161,"name":26672,"oldSlug":26673,"orderRank":26674,"reviewer":161,"sections":26675,"seo":161,"slug":26865,"tags":26866},"2026-01-15T16:11:53Z","4d632777-21db-4e39-961d-42a239deb52b","7hw4Cb1llohacCi9MHykoF",{"base":26656},{"id":26653,"rev":26657},"2oGVswEwQBfyYUvi7k5ztL","2026-01-28T08:49:46Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":26660,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":26662,"uid":54},{"base":26661},{"id":45,"rev":49},{"_type":17,"current":54},[26664],{"_key":26665,"_type":99,"children":26666,"markDefs":26671,"style":107},"3fbac26d4d9c",[26667],{"_key":26668,"_type":103,"marks":26669,"text":26670},"47a8f0f9ea21",[],"Artificial Intelligence offers a wide range of applications in business, from workflow management to trend forecasting. However, when it comes to the manufacturing industry, there",[],"AI-based Predictive Maintenance","ai-based-predictive-maintenance","0|1000p4:",[26676],{"_createdAt":26677,"_id":26678,"_key":26679,"_ref":26678,"_rev":26657,"_type":168,"_updatedAt":26677,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":26680,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:35Z","d7d6u86Zy071KG7nHItWQ","Ozv4fyjk7imZc50z7eckX",[26681,26694,26701,26708,26715,26722,26729,26736,26743,26750,26757,26764,26771,26778,26785,26792,26799,26806,26813,26820,26827,26834,26840,26847,26854],{"_key":26682,"_type":99,"children":26683,"markDefs":26691,"style":799},"bScYj8nTH1iQLhTZcAe5c",[26684,26688],{"_type":103,"marks":26685,"text":26687},[26686],"oiWDo2YLw9BDAYpTKtiYU","Artificial Intelligence",{"_type":103,"marks":26689,"text":26690},[]," offers a wide range of applications in business, from workflow management to trend forecasting. However, when it comes to the manufacturing industry, there is one concept that stands out – Predictive Maintenance. Through it businesses are able to use their data not only for reporting the past but also to predict the future.",[26692],{"_key":26686,"_type":173,"href":26693},"https://cosmosthrace.com/how-ai-and-ml-can-unleash-the-potential-of-manufacturing/",{"_key":26695,"_type":99,"children":26696,"markDefs":26700,"style":170},"Qay5IhtX5Wka5p05hXrHK",[26697],{"_type":103,"marks":26698,"text":26699},[],"What is Predictive Maintenance?",[],{"_key":26702,"_type":99,"children":26703,"markDefs":26707,"style":799},"vRft1qikOQzOx3M7FcgZt",[26704],{"_type":103,"marks":26705,"text":26706},[],"Predictive maintenance is a term used in AI and machine learning to describe the capacity to use large amounts of data to forecast and point out possible issues. Sensors detect errors before they lead to failures in operation processes or systems. Having robust predictive maintenance technologies in place, allows organizations to foresee when and where possible service breakdowns may occur. Hence, they can react accordingly and quickly to avoid service interruptions.",[],{"_key":26709,"_type":99,"children":26710,"markDefs":26714,"style":170},"13EFyT4LquIqvDOhNVlVO",[26711],{"_type":103,"marks":26712,"text":26713},[],"What are the benefits of adopting Predictive Maintenance?",[],{"_key":26716,"_type":99,"children":26717,"markDefs":26721,"style":799},"xghZLcFCJ_k31HpzL-jfp",[26718],{"_type":103,"marks":26719,"text":26720},[],"The implementation of Predictive Maintenance can be done in accordance with the company’s needs and preferences. They can vary from complex data gathering and model building to simple computations. Either way, predictive maintenance tools are used by companies to maintain critical assets to work efficiently and effectively. Therefore, the following goals are reached:",[],{"_key":26723,"_type":99,"children":26724,"level":230,"listItem":231,"markDefs":26728,"style":107},"Uwyq8-moDfHnKv4ofAHy_",[26725],{"_type":103,"marks":26726,"text":26727},[],"Revenues increase as productivity increases and costs for new materials decrease.",[],{"_key":26730,"_type":99,"children":26731,"level":230,"listItem":231,"markDefs":26735,"style":107},"aZLGrQztAZ7OkqO6d5Gal",[26732],{"_type":103,"marks":26733,"text":26734},[],"Operational expenses decrease and the risk of unplanned failures reduces.",[],{"_key":26737,"_type":99,"children":26738,"level":230,"listItem":231,"markDefs":26742,"style":107},"UHC9LgYUCEIXzcHSLz4I7",[26739],{"_type":103,"marks":26740,"text":26741},[],"Equipment life cycle is extended and improved.",[],{"_key":26744,"_type":99,"children":26745,"level":230,"listItem":231,"markDefs":26749,"style":107},"xxWaFcs0bcEPTPmcoIuYK",[26746],{"_type":103,"marks":26747,"text":26748},[],"Repetitive rework is minimized, possible defects decrease, and quality increases.",[],{"_key":26751,"_type":99,"children":26752,"level":230,"listItem":231,"markDefs":26756,"style":107},"DklXCGj_fzRBaDcJeM3Tj",[26753],{"_type":103,"marks":26754,"text":26755},[],"Safety and energy efficiency increase.",[],{"_key":26758,"_type":99,"children":26759,"level":230,"listItem":231,"markDefs":26763,"style":107},"truzpPLQ-V2REdnHd3Wxw",[26760],{"_type":103,"marks":26761,"text":26762},[],"Keeping supply chains intact. ",[],{"_key":26765,"_type":99,"children":26766,"markDefs":26770,"style":170},"LckQifFr6sxrORquJgrFm",[26767],{"_type":103,"marks":26768,"text":26769},[],"How does it work?",[],{"_key":26772,"_type":99,"children":26773,"markDefs":26777,"style":799},"o66jkmQDt1Fh_6byQSTKq",[26774],{"_type":103,"marks":26775,"text":26776},[],"The process begins with the analysis of the business case – what the pain point in terms of costs is and how AI would improve it. Then, Machine Learning (ML) is infrastructured in data research and data collection. The following stage is to train the ML to recognize areas of errors and how to address them. The desired outcomes are for predictive maintenance to provide coherent and accurate information. ",[],{"_key":26779,"_type":99,"children":26780,"markDefs":26784,"style":799},"06WzsNWh2Itrw9UGm96Te",[26781],{"_type":103,"marks":26782,"text":26783},[],"To illustrate the whole process by breaking it into seven more detailed stages, the timetable would be as follows:",[],{"_key":26786,"_type":99,"children":26787,"level":230,"listItem":4889,"markDefs":26791,"style":107},"fPlk6l5M68r5UheLa09xQ",[26788],{"_type":103,"marks":26789,"text":26790},[],"Understand the need – consider the costs, wastes, and inefficiency; then, identify the optimal case for the business.",[],{"_key":26793,"_type":99,"children":26794,"level":230,"listItem":4889,"markDefs":26798,"style":107},"1_62vSL1St2azM8IPEE8w",[26795],{"_type":103,"marks":26796,"text":26797},[],"Extract data – allow the technology to have access to the data collectors and storage.",[],{"_key":26800,"_type":99,"children":26801,"level":230,"listItem":4889,"markDefs":26805,"style":107},"6r7cpiKFOsPd_RQhPkJo4",[26802],{"_type":103,"marks":26803,"text":26804},[],"Explore, analyze and delete data – use only relevant and understandable data.",[],{"_key":26807,"_type":99,"children":26808,"level":230,"listItem":4889,"markDefs":26812,"style":107},"MbjpNoA5nyQlU8I9HWzJ9",[26809],{"_type":103,"marks":26810,"text":26811},[],"Enrich data – manipulate the data so that the sensors could address it as one unit rather than separated parts.",[],{"_key":26814,"_type":99,"children":26815,"level":230,"listItem":4889,"markDefs":26819,"style":107},"Ygbw6cGN2Jcg5Y-syypb_",[26816],{"_type":103,"marks":26817,"text":26818},[],"Predict – use all the collected data and sources to create a predictive model.",[],{"_key":26821,"_type":99,"children":26822,"level":230,"listItem":4889,"markDefs":26826,"style":107},"wOyJ77tSGnzG8eVGIujam",[26823],{"_type":103,"marks":26824,"text":26825},[],"Get visualized – the feedback is received as a product from the model which helps managers to react accordingly.",[],{"_key":26828,"_type":99,"children":26829,"level":230,"listItem":4889,"markDefs":26833,"style":107},"p6SSg8ebn_6U6eqfja3gU",[26830],{"_type":103,"marks":26831,"text":26832},[],"Execute – start using the model in real-time cases.",[],{"_key":26835,"_type":99,"children":26836,"markDefs":26839,"style":170},"IvijDL62ID810taMS5-V_",[26837],{"_type":103,"marks":26838,"text":4733},[],[],{"_key":26841,"_type":99,"children":26842,"markDefs":26846,"style":799},"rbshP_lQlcgQ5s06tLbyF",[26843],{"_type":103,"marks":26844,"text":26845},[],"The most immediate benefits from implementing Predictive Maintenance are both cost reduction and an increase in quality. 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It assists salespeople in prioritizing tasks so that they may concentrate on the high-probabilities, high-payoff prospects, and, namely, clients that are most important to them. AI can also give insights on sales representative-to-potential-client communications, such as emails, phone calls, and chats. In addition, AI optimizes sales forecasting, lead qualifying, routing/matching, and consulting sales/customer care representatives.",[],{"_key":26945,"_type":99,"children":26946,"markDefs":26950,"style":170},"FIWVTsj35k1m7TKMZWdil",[26947],{"_type":103,"marks":26948,"text":26949},[],"Not only are sales and revenues boosted, but AI also enhances contact centers’ efficiency.",[],{"_key":26952,"_type":99,"children":26953,"markDefs":26957,"style":799},"esmGunDzjnKIZQss7rhuF",[26954],{"_type":103,"marks":26955,"text":26956},[],"Predictive call routing improves customer experience by analyzing prior customer behavior and preferences. By deploying this AI solution, sales representatives and customer service agents can forecast the abilities and personality qualities required to give the best possible service. In this case, AI reduces escalation time and improves the overall satisfaction of both the caller and the agent. ",[],{"_key":26959,"_type":99,"children":26960,"markDefs":26964,"style":799},"yGwSyr6qCUEfVMsZzveat",[26961],{"_type":103,"marks":26962,"text":26963},[],"Furthermore, there is the issue of contact centers facing the difficulty of training large numbers of agents. Agent growth and coaching are major priorities, and AI may help by assessing agent data and caller replies to offer customized on-demand learning and promote advanced performance. 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This is an important but often overlooked aspect of customer experience and sales performance. ",[],{"_key":26980,"_type":99,"children":26981,"markDefs":26985,"style":799},"uMPO5sJ6ISZy45vOTK7bz",[26982],{"_type":103,"marks":26983,"text":26984},[],"A key takeaway is that, AI will become increasingly valuable to customer experience (CX), customer satisfaction (CS), and sales teams. 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",[27300],{"_key":27294,"_type":173,"href":27301},"https://www.alltheresearch.com/report/314/artificial-intelligence-ai-in-logistics-and-supply-chain-market-ecosystem",{"_key":27303,"_type":99,"children":27304,"markDefs":27319,"style":799},"GUXK5F5n2-CB6WabaLe24",[27305,27308,27311,27314,27317],{"_type":103,"marks":27306,"text":27307},[],"If you are looking for a way to maximize warehouse and sales efficiently, contact the professionals at ",{"_type":103,"marks":27309,"text":7898},[27310],"vTagVofx7ZeHiPfPmKGqR",{"_type":103,"marks":27312,"text":27313},[]," or take a look at our ",{"_type":103,"marks":27315,"text":22133},[27316],"VxB-KiBrpEdI1adqxPQzu",{"_type":103,"marks":27318,"text":22136},[],[27320,27321],{"_key":27310,"_type":173,"href":18723},{"_key":27316,"_type":173,"href":19377},{"_type":17,"current":27154},[27324,27325,27332],{"_createdAt":24375,"_id":24376,"_rev":24377,"_type":8636,"_updatedAt":24378,"name":24379,"orderRank":13966,"uid":24380},{"_createdAt":27326,"_id":27327,"_rev":27328,"_type":8636,"_updatedAt":27329,"name":27330,"orderRank":14579,"uid":27331},"2026-01-20T12:26:31Z","4ab0e20e-9f68-4348-af3d-d90effe04d1c","n91tOxoMUaPULCyHfFzw1R","2026-01-20T12:26:34Z","Supply Chain","supply-chain",{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":27334,"_id":27335,"_rev":27336,"_system":27337,"_type":72,"_updatedAt":27340,"archived":126,"author":161,"category":27341,"date":27143,"description":27345,"image":161,"name":27354,"oldSlug":27355,"orderRank":27356,"reviewer":161,"sections":27357,"seo":161,"slug":27564,"tags":27565},"2026-01-15T16:05:01Z","3321b32e-60bd-40cc-bf06-17aaf050ffdd","ir9xdmjsDvNqVMLz9XnCjW",{"base":27338},{"id":27335,"rev":27339},"YkA36qTDOerM1fSJama8F9","2026-01-28T08:41:28Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":27342,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":27344,"uid":54},{"base":27343},{"id":45,"rev":49},{"_type":17,"current":54},[27346],{"_key":27347,"_type":99,"children":27348,"markDefs":27353,"style":107},"98c7052ac301",[27349],{"_key":27350,"_type":103,"marks":27351,"text":27352},"9607809655a6",[],"350 Distribution Centers in the US and UK participated in an independent research study. The findings? Most of them use AI in some area of",[],"AI Powered Optimization for Distribution Centers","ai-optimization-for-distribution-centers","0|1000lk:",[27358],{"_createdAt":27359,"_id":27360,"_key":27361,"_ref":27360,"_rev":27339,"_type":168,"_updatedAt":27359,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":27362,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:16Z","NoMdITOB6jFM8VrpJC5y3","fUWQ3CXaaSm4dO1Td-xp9",[27363,27370,27377,27384,27391,27398,27405,27412,27419,27426,27433,27440,27447,27454,27461,27468,27482,27489,27496,27512,27519,27526,27533,27540,27547],{"_key":27364,"_type":99,"children":27365,"markDefs":27369,"style":799},"7tS4aaA8ofAxBuBaItkzU",[27366],{"_type":103,"marks":27367,"text":27368},[],"350 Distribution Centers in the US and UK participated in an independent research study. The findings? ",[],{"_key":27371,"_type":99,"children":27372,"markDefs":27376,"style":799},"Qfky7Ww9MErCxwGQP6IC1",[27373],{"_type":103,"marks":27374,"text":27375},[],"However, no beating around the bush, the key issues noted were cost, complexity, and lack of understanding of how to use AI properly.",[],{"_key":27378,"_type":99,"children":27379,"markDefs":27383,"style":170},"nmAygeHrvUPdvxycy9QH4",[27380],{"_type":103,"marks":27381,"text":27382},[],"Why do distribution centers use AI?",[],{"_key":27385,"_type":99,"children":27386,"markDefs":27390,"style":799},"6u1KROfRElfRbqcarEPCr",[27387],{"_type":103,"marks":27388,"text":27389},[],"The warehouse automation market has been growing steadily and experts expect it to reach some 30 Billion USD by 2026. The pandemic has helped this growth, as it drives improvements in supply chains, and thus in distribution centers. Growth in eCommerce, expensive and hard-to-find physical labor and increased customer expectations all lead to investments in automation. Good data is also a necessity of AI, and distribution centers are perfect environments for collecting large datasets. ",[],{"_key":27392,"_type":99,"children":27393,"markDefs":27397,"style":799},"AQVUEcjOjSxytR2G927SQ",[27394],{"_type":103,"marks":27395,"text":27396},[],"Certainly however, there is a consensus on the fact that AI is the future as they bring numerous benefits to businesses, such as: ",[],{"_key":27399,"_type":99,"children":27400,"markDefs":27404,"style":170},"k_wkc_Imfre4wcgUaFvwv",[27401],{"_type":103,"marks":27402,"text":27403},[],"AI Optimization for Distribution Centers:",[],{"_key":27406,"_type":99,"children":27407,"level":230,"listItem":231,"markDefs":27411,"style":107},"uH7TkVvRlYFXPTDGZQQt6",[27408],{"_type":103,"marks":27409,"text":27410},[],"Lower labor costs;",[],{"_key":27413,"_type":99,"children":27414,"level":230,"listItem":231,"markDefs":27418,"style":107},"9lFGU6crHCkcnpetN8BIJ",[27415],{"_type":103,"marks":27416,"text":27417},[],"Dynamic Slotting – fully automated and optimized, with lower costs as no in-depth CAD drawing is required;",[],{"_key":27420,"_type":99,"children":27421,"level":230,"listItem":231,"markDefs":27425,"style":107},"-8PQ5acujNQgenJioaRNl",[27422],{"_type":103,"marks":27423,"text":27424},[],"Higher employee satisfaction;",[],{"_key":27427,"_type":99,"children":27428,"level":230,"listItem":231,"markDefs":27432,"style":107},"5ucNkbZLMu94yZ6qoezTX",[27429],{"_type":103,"marks":27430,"text":27431},[],"Production output;",[],{"_key":27434,"_type":99,"children":27435,"level":230,"listItem":231,"markDefs":27439,"style":107},"uS--7aY1biMX6ATThe_L9",[27436],{"_type":103,"marks":27437,"text":27438},[],"Automatic workflow orchestration;",[],{"_key":27441,"_type":99,"children":27442,"level":230,"listItem":231,"markDefs":27446,"style":107},"gSP067QH6bxxUnx34r3AS",[27443],{"_type":103,"marks":27444,"text":27445},[],"Safety;",[],{"_key":27448,"_type":99,"children":27449,"level":230,"listItem":231,"markDefs":27453,"style":107},"Mgh_4F_JcraUy8-JGrFRL",[27450],{"_type":103,"marks":27451,"text":27452},[],"Management effectiveness and better Performance Management;",[],{"_key":27455,"_type":99,"children":27456,"level":230,"listItem":231,"markDefs":27460,"style":107},"KRujCsp4m_13SHP1EHJpY",[27457],{"_type":103,"marks":27458,"text":27459},[],"In-Warehouse Travel Optimization – it is indicated that 30% of labor costs are attributed to time spent navigating a warehouse inefficiently.",[],{"_key":27462,"_type":99,"children":27463,"markDefs":27467,"style":799},"LfRJP5rOYur2dazR0d9GH",[27464],{"_type":103,"marks":27465,"text":27466},[],"A more futuristic implementation of AI in distribution centers and warehouses is wearable technology. Natural language processing enables voice picking. Smart glasses that automatically scan barcodes and other technology that is still in the testing stage will soon be on the scene.",[],{"_key":27469,"_type":99,"children":27470,"markDefs":27479,"style":799},"D90BWQ2d4CSibcDXobr1a",[27471,27474,27477],{"_type":103,"marks":27472,"text":27473},[],"Read our in-depth look into the benefits of AI in warehousing ",{"_type":103,"marks":27475,"text":4754},[27476],"KQJa-4JQuNvepW1z813kC",{"_type":103,"marks":27478,"text":793},[],[27480],{"_key":27476,"_type":173,"href":27481},"https://cosmosthrace.com/top-5-applications-of-ai-in-supply-chain/",{"_key":27483,"_type":99,"children":27484,"markDefs":27488,"style":170},"jW2KUgXAd1GGTCOtpDQYH",[27485],{"_type":103,"marks":27486,"text":27487},[],"Issues with implementing AI:",[],{"_key":27490,"_type":99,"children":27491,"markDefs":27495,"style":799},"j_PYerlGGzh6cWt1JY7mv",[27492],{"_type":103,"marks":27493,"text":27494},[],"While many benefits exist, 99% of organizations say they find it difficult to use AI efficiently. On top of that, 80% state that there is a lack of understanding of how to put AI into practice. ",[],{"_key":27497,"_type":99,"children":27498,"markDefs":27509,"style":799},"46b2rG_79_eRCLngPfB8y",[27499,27502,27506],{"_type":103,"marks":27500,"text":27501},[],"The MHI Annual Industry ",{"_type":103,"marks":27503,"text":27505},[27504],"RttlszoPytFeKunyU3uCh","Report",{"_type":103,"marks":27507,"text":27508},[]," 2020 finds that only 12% of the respondents in the Supply Chain Industry are using AI tech.",[27510],{"_key":27504,"_type":173,"href":27511},"https://www.mhi.org/publications/report",{"_key":27513,"_type":99,"children":27514,"markDefs":27518,"style":170},"OlB7tWNbWV0crxtO1Id9U",[27515],{"_type":103,"marks":27516,"text":27517},[],"The reasons:",[],{"_key":27520,"_type":99,"children":27521,"level":230,"listItem":231,"markDefs":27525,"style":107},"hwVLXhLVk-E3-KmWFw5s7",[27522],{"_type":103,"marks":27523,"text":27524},[],"Perception of high cost to benefit ratio;",[],{"_key":27527,"_type":99,"children":27528,"level":230,"listItem":231,"markDefs":27532,"style":107},"gQnzsImQIGL1MwIQiDAPl",[27529],{"_type":103,"marks":27530,"text":27531},[],"Issues with Risk and control operation decisions;",[],{"_key":27534,"_type":99,"children":27535,"level":230,"listItem":231,"markDefs":27539,"style":107},"NYZJi1NKrnIfCfwAomJCm",[27536],{"_type":103,"marks":27537,"text":27538},[],"Time and monetary costs of training;",[],{"_key":27541,"_type":99,"children":27542,"level":230,"listItem":231,"markDefs":27546,"style":107},"BVhkOGgTowv1FKWTfxacj",[27543],{"_type":103,"marks":27544,"text":27545},[],"Lack of understanding for implementation. ",[],{"_key":27548,"_type":99,"children":27549,"markDefs":27561,"style":799},"8Tc_VZ_29bGZV7MPbS-Nn",[27550,27553,27556,27559],{"_type":103,"marks":27551,"text":7898},[27552],"m12i7O4GJBRvEz8X-LO0m",{"_type":103,"marks":27554,"text":27555},[]," is there to help in the implementation, integration, and support of AI in the distribution center. But most importantly, we aim to help inform people about the benefits of the technology. Contact us to find out how we can help on your journey to automation or look at our portfolio of ",{"_type":103,"marks":27557,"text":19370},[27558],"Hazd2em2SvsqCC59UBFnL",{"_type":103,"marks":27560,"text":793},[],[27562,27563],{"_key":27552,"_type":173,"href":18723},{"_key":27558,"_type":173,"href":19377},{"_type":17,"current":27355},[27566,27567,27568],{"_createdAt":24375,"_id":24376,"_rev":24377,"_type":8636,"_updatedAt":24378,"name":24379,"orderRank":13966,"uid":24380},{"_createdAt":27326,"_id":27327,"_rev":27328,"_type":8636,"_updatedAt":27329,"name":27330,"orderRank":14579,"uid":27331},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":27570,"_id":27571,"_rev":27572,"_system":27573,"_type":72,"_updatedAt":27576,"archived":126,"author":161,"category":27577,"date":27143,"description":27581,"image":161,"name":27590,"oldSlug":27591,"orderRank":27592,"reviewer":161,"sections":27593,"seo":161,"slug":27719,"tags":27720},"2026-01-15T15:59:30Z","7426b8cd-d1dc-4018-a548-a416214f688a","7hw4Cb1llohacCi9MHoxTX",{"base":27574},{"id":27571,"rev":27575},"YkA36qTDOerM1fSJamXwZL","2026-01-28T08:15:52Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":27578,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":27580,"uid":30},{"base":27579},{"id":21,"rev":25},{"_type":17,"current":30},[27582],{"_key":27583,"_type":99,"children":27584,"markDefs":27589,"style":107},"f1f767bc280e",[27585],{"_key":27586,"_type":103,"marks":27587,"text":27588},"e996daa2a159",[],"In the highly digitalized business world and the high-sky demand for talent, recruiters must rely on the assistance of AI and automation to solve hiring",[],"How can AI solve the talent shortage challenge?","how-can-ai-and-talent-shortage-challenge","0|1000iw:",[27594],{"_createdAt":27595,"_id":27596,"_key":27597,"_ref":27596,"_rev":27575,"_type":168,"_updatedAt":27595,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":27598,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:57Z","e01CnVOnjod8c46y1lQEU","3Tf_nX-mL3as-qAWZUUxe",[27599,27609,27616,27623,27630,27637,27644,27651,27658,27674,27681,27688,27709],{"_key":27600,"_type":99,"children":27601,"markDefs":27605,"style":799},"suR8mVX77yQDu_kTUUe4b",[27602],{"_type":103,"marks":27603,"text":27604},[],"In the highly digitalized business world and the high-sky demand for talent, recruiters must rely on the assistance of AI and automation to solve hiring issues and fill crucial posts quickly in a competitive labor market. How is that possible? In other words, this article will look at how AI technology can solve the talent shortage challenge.",[27606],{"_key":27607,"_type":173,"href":27608},"IDdPW7Ea4p_qfD-N6mdEy","javascript:void(0)",{"_key":27610,"_type":99,"children":27611,"markDefs":27615,"style":799},"_2nKlE8N6HJYn2XAlAV8M",[27612],{"_type":103,"marks":27613,"text":27614},[],"Employers and HR professionals must reimagine talent experiences to gain a competitive advantage. AI and automation may help companies achieve this aim by providing hyper-personalization that boosts productivity. At the same time, they can also provide a competitive talent data intelligence system. Moreover, HR directors now have an even larger potential to enable employee migration inside their businesses, grow internal sourcing, and minimize time-to-fill with the use of AI technology.",[],{"_key":27617,"_type":99,"children":27618,"markDefs":27622,"style":170},"M8ESVbEjDKMcjYNXn4dTN",[27619],{"_type":103,"marks":27620,"text":27621},[],"How and where to start on the journey of AI combating talent scarcity?",[],{"_key":27624,"_type":99,"children":27625,"markDefs":27629,"style":799},"bM10Q0mIcO1UBb7BmDoD_",[27626],{"_type":103,"marks":27627,"text":27628},[],"To fulfill current talent expectations, companies and HR professionals must first build their competitive advantage. They can do this by rethinking talent experiences and considering how a comprehensive approach to the talent experience may help them. In fact, considering how vital the culture of advancement is for a business, HR teams, managers, and leaderships think that this is where they should begin to inspire talent to stay. Motivation, development, and a sense of progress have always been among the top reasons why employees remain in business.",[],{"_key":27631,"_type":99,"children":27632,"markDefs":27636,"style":799},"gBR6UJzifmBrO8l1zT8eh",[27633],{"_type":103,"marks":27634,"text":27635},[],"The way automation fits into the development of such culture is through making recruiters comfortable with internal mobility and recruitment. There must be a normality of providing possibilities for internal advancements. Hence, AI can assist employees, executives, and recruiters in advance more naturally and smoothly.",[],{"_key":27638,"_type":99,"children":27639,"markDefs":27643,"style":170},"vVoVnR9yElKzyVg4Y35IX",[27640],{"_type":103,"marks":27641,"text":27642},[],"However, we should also consider recruiting talent shortage when speaking of talent scarcity.",[],{"_key":27645,"_type":99,"children":27646,"markDefs":27650,"style":799},"6pIDaQaonzng_zGi_dFKr",[27647],{"_type":103,"marks":27648,"text":27649},[],"The business world has reached the point of the necessity for HR departments to embrace AI and automation. In other words, AI’s purpose is not to take people’s jobs or fill in the gaps when hiring is difficult, but to assist recruiters in managing processes. These are the manual, time-consuming tasks that prevent them from truly adding value to the recruiting and onboarding process. Therefore, the value of AI lies in its ability to relieve recruiting staff of tasks such as scheduling and screening, allowing them to focus on advising hiring managers.",[],{"_key":27652,"_type":99,"children":27653,"markDefs":27657,"style":170},"8Ppk-YTOBoBQetpHtqkxz",[27654],{"_type":103,"marks":27655,"text":27656},[],"Ethical considerations attached to the concept of automating recruiting processes.",[],{"_key":27659,"_type":99,"children":27660,"markDefs":27671,"style":799},"NbYG1uO1BSS6PWFWB0mW-",[27661,27664,27668],{"_type":103,"marks":27662,"text":27663},[],"There is a lot of ambiguity about AI and its capacity to eliminate and create prejudice. Thus, there is a lot of interest in learning how HR teams may use ",{"_type":103,"marks":27665,"text":27667},[27666],"ohTwFxsxU0Jcqbc6kTzgG","AI ethically",{"_type":103,"marks":27669,"text":27670},[]," and avoid bias.",[27672],{"_key":27666,"_type":173,"href":27673},"https://cosmosthrace.com/the-moral-principles-behind-ai-technology/",{"_key":27675,"_type":99,"children":27676,"markDefs":27680,"style":799},"FwOnWyPKewDmtJXV8hXaM",[27677],{"_type":103,"marks":27678,"text":27679},[],"No algorithm is intrinsically ethical or unethical since AI learns on current data sets that are developed and shaped by human activity. Transparency must be at the heart of AI systems for them to function ethically. In that way, nobody, regardless of their expertise in machine learning, can comprehend the algorithm makes a decision. Hence, smart machines should be dealt with accordingly to address malfunctioning scenarios in ethical choices and prevent the misuse of ethical requirements in their performance.",[],{"_key":27682,"_type":99,"children":27683,"markDefs":27687,"style":799},"20uTXRqcc1Y6yHN68XR2s",[27684],{"_type":103,"marks":27685,"text":27686},[],"Many businesses can benefit from arming organizations with technology that can automate time-consuming recruiting processes. Not only that but it can also provide individualized experiences and advancement possibilities to the top candidates and internal workers. AI solutions optimize the performance in industries and the talent shortage challenge should not be left alone. The good thing is that both sides (managers and employees) can benefit from the use of automation. Moreover, they can explore even further the possibilities of finding the perfect fit for the company.",[],{"_key":27689,"_type":99,"children":27690,"markDefs":27706,"style":799},"7hoJ9uGW8tlFYEFPG0upD",[27691,27694,27698,27701,27704],{"_type":103,"marks":27692,"text":27693},[],"Let us allow your data to help you in your hiring process! ",{"_type":103,"marks":27695,"text":27697},[27696],"dzgFdxyFjImfWKacLEnZE","Book a free call now",{"_type":103,"marks":27699,"text":27700},[]," or take a look at our portfolio of ",{"_type":103,"marks":27702,"text":19370},[27703],"dCMHwnL9Vi8nMvETxVZnz",{"_type":103,"marks":27705,"text":20704},[],[27707,27708],{"_key":27696,"_type":173,"href":19536},{"_key":27703,"_type":173,"href":19377},{"_key":27710,"_type":99,"children":27711,"markDefs":27716,"style":799},"MG6WtYFuDLGZrOL0Y_-6K",[27712],{"_type":103,"marks":27713,"text":27715},[27714],"TrUsgFjB2n5UnMdc2Fkh1","Source",[27717],{"_key":27714,"_type":173,"href":27718},"https://www.unleash.ai/artificial-intelligence/leveraging-the-power-of-ai-to-help-best-fit-candidates-find-the-right-job-faster/",{"_type":17,"current":27591},[27721],{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":27723,"_id":27724,"_rev":27725,"_system":27726,"_type":72,"_updatedAt":27729,"archived":126,"author":161,"category":27730,"date":27143,"description":27734,"image":161,"name":27743,"oldSlug":27744,"orderRank":27745,"reviewer":161,"sections":27746,"seo":161,"slug":27845,"tags":27846},"2026-01-15T16:13:39Z","98ed0399-673d-4e35-ba3b-cdee4510b3e9","iywjT5idYMWZvttqpuzARe",{"base":27727},{"id":27724,"rev":27728},"YkA36qTDOerM1fSJamcOrX","2026-01-28T08:07:36Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":27731,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":27733,"uid":30},{"base":27732},{"id":21,"rev":25},{"_type":17,"current":30},[27735],{"_key":27736,"_type":99,"children":27737,"markDefs":27742,"style":107},"694d55249119",[27738],{"_key":27739,"_type":103,"marks":27740,"text":27741},"3b5edcfb008c",[],"The possibility for a clash between Artificial Intelligence and Human Rights rises as people become more reliant on robots to enhance the effectiveness of operations",[],"Is AI a Threat to Human Rights","is-ai-a-threat-to-human-rights","0|1000qg:",[27747],{"_createdAt":27748,"_id":27749,"_key":27750,"_ref":27749,"_rev":27728,"_type":168,"_updatedAt":27748,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":27751,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:42:03Z","IYpFf9Cj6EHRAB0c83abh","yxP6iCIJZG-082s8v87eB",[27752,27766,27773,27783,27793,27803,27810,27817,27824],{"_key":27753,"_type":99,"children":27754,"markDefs":27764,"style":799},"BL50oX0xg71TOQP-zbrwx",[27755,27758,27761],{"_type":103,"marks":27756,"text":27757},[],"The possibility for a clash between ",{"_type":103,"marks":27759,"text":26687},[27760],"WzyH_3Q3OpXFMazRnWa-S",{"_type":103,"marks":27762,"text":27763},[]," and Human Rights rises as people become more reliant on robots to enhance the effectiveness of operations and make informed decisions. Artificial Intelligence, if left unregulated, has the potential to cause inequity and even be used to actively violate human rights around the world. However, when utilized properly, AI can improve human rights, promote shared development, and help us all have a better future. So, in general – is AI a threat to human rights?",[27765],{"_key":27760,"_type":173,"href":27673},{"_key":27767,"_type":99,"children":27768,"markDefs":27772,"style":170},"3USZW2Wb_2osPkL1f1ep1",[27769],{"_type":103,"marks":27770,"text":27771},[],"Threats and challenges related to AI:",[],{"_key":27774,"_type":99,"children":27775,"level":230,"listItem":231,"markDefs":27782,"style":107},"4RgQc7sKvhE1BaL0WscaH",[27776,27779],{"_type":103,"marks":27777,"text":27778},[3055],"Threat to employers:",{"_type":103,"marks":27780,"text":27781},[]," Undoubtedly, the use of AI boosts productivity and efficiency to extreme levels. Moreover, AI is now replacing even some higher-order tasks, such as driving or filling prescriptions. Thus, AI implementation could lead to a huge exodus of workers. Automation, on the other hand, does not always have to be a net negative for the workforce; it can often have a positive impact on it by spurring economic growth and lowering prices. As a result, this same workforce can be transitioned to new tasks that require higher-level thinking and soft skills, in this sense – interpersonal skills and emotional intelligence.",[],{"_key":27784,"_type":99,"children":27785,"level":230,"listItem":231,"markDefs":27792,"style":107},"LO1-E5Qlmv71pRmsUGmBS",[27786,27789],{"_type":103,"marks":27787,"text":27788},[3055],"Threats to privacy",{"_type":103,"marks":27790,"text":27791},[],": are another issue when it comes to AI. AI collects and extrapolates huge volumes of data, including streams of data from mobile devices and other gadgets. When businesses have vast amounts of data about their consumers and competitors, the right to privacy may be jeopardized. Especially as AI advances and new ways to use personal data emerge. Additional precautions, such as data anonymization techniques or actively screening algorithms for privacy vulnerabilities, should be implemented by companies that want to prevent violating privacy.",[],{"_key":27794,"_type":99,"children":27795,"level":230,"listItem":231,"markDefs":27802,"style":107},"mi4NN-08AOVDSsIyK-xLX",[27796,27799],{"_type":103,"marks":27797,"text":27798},[3055],"Threat to job seekers",{"_type":103,"marks":27800,"text":27801},[],": Yes, and no. For instance, if an organization gets information from public records, it should avoid making assumptions about possible candidates’ personalities and/or skills purely based on this sample information. When a human assessment is combined with AI, it may more accurately determine whether a candidate meets the company’s requirements. A good practice for companies is to unite human consciousness with AI to guarantee a lack of discrimination.",[],{"_key":27804,"_type":99,"children":27805,"markDefs":27809,"style":170},"0Iu55hkrLoDIjyLmRvaD6",[27806],{"_type":103,"marks":27807,"text":27808},[],"What’s next for AI and Human Rights?",[],{"_key":27811,"_type":99,"children":27812,"markDefs":27816,"style":799},"YJdsQcy-afbqP7Xob11CF",[27813],{"_type":103,"marks":27814,"text":27815},[],"To cover everything, businesses that seek ways to establish trust in their customers should be honest and transparent. Companies worldwide may often appeal to a bigger set of consumers and maintain their existing clients by adopting technology and being upfront about how the firm makes decisions. The implementation of AI should come along with implementing additional measures to reduce the danger of prejudice. Companies can take additional precautions to protect their users’ privacy, or their employees fear becoming unemployed.",[],{"_key":27818,"_type":99,"children":27819,"markDefs":27823,"style":799},"TANTttUYlPbs5NE4JsL-D",[27820],{"_type":103,"marks":27821,"text":27822},[],"By being aware of the potential human rights risks, leaders can utilize AI to improve their business and drive productivity. At the same time, they can avoid some of the negative repercussions that AI may bring. We hope that this information helps you answer the question “Is AI a threat to Human Rights”.",[],{"_key":27825,"_type":99,"children":27826,"markDefs":27842,"style":799},"pg-B5vNr59W5oDPDTjhS4",[27827,27830,27833,27836,27839],{"_type":103,"marks":27828,"text":27829},[],"If you want to learn more about Artificial Intelligence, ",{"_type":103,"marks":27831,"text":26325},[27832],"Fjv_HCeOQ2OI8rnT5EGzh",{"_type":103,"marks":27834,"text":27835},[]," with us! You can also take a look at our full portfolio of ",{"_type":103,"marks":27837,"text":19370},[27838],"9vPwcObwTiCTipaUsZEiS",{"_type":103,"marks":27840,"text":27841},[],". ",[27843,27844],{"_key":27832,"_type":173,"href":19536},{"_key":27838,"_type":173,"href":19377},{"_type":17,"current":27744},[27847,27848],{"_createdAt":13100,"_id":13101,"_rev":13102,"_type":8636,"_updatedAt":13103,"name":13104,"orderRank":12215,"uid":13105},{"_createdAt":10732,"_id":10733,"_rev":10734,"_type":8636,"_updatedAt":10735,"name":10736,"orderRank":10737,"uid":10738},{"_createdAt":27850,"_id":27851,"_rev":27852,"_system":27853,"_type":72,"_updatedAt":27856,"archived":126,"author":161,"category":27857,"date":27143,"description":27861,"image":161,"name":27870,"oldSlug":27871,"orderRank":27872,"reviewer":161,"sections":27873,"seo":161,"slug":27994,"tags":27995},"2026-01-15T16:13:09Z","b9244f97-3773-4137-a535-8a81bc243f67","3x1HJiv3wwU7cYVoHssvQi",{"base":27854},{"id":27851,"rev":27855},"YkA36qTDOerM1fSJamcMmC","2026-01-28T08:05:12Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":27858,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":27860,"uid":30},{"base":27859},{"id":21,"rev":25},{"_type":17,"current":30},[27862],{"_key":27863,"_type":99,"children":27864,"markDefs":27869,"style":107},"e01554c28150",[27865],{"_key":27866,"_type":103,"marks":27867,"text":27868},"bee716016e28",[],"Artificial intelligence (AI) and robots are digital technologies that already have and will continue to have a major influence on humanity’s progress and development.",[],"The moral principles behind AI technology","the-moral-principles-behind-ai-technology","0|1000q0:",[27874],{"_createdAt":27875,"_id":27876,"_key":27877,"_ref":27876,"_rev":27855,"_type":168,"_updatedAt":27875,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":27878,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:42:01Z","qOwGVDxIsJBHwmrhNvOJk","NxhfXxuFFloKu4EdP8bPt",[27879,27886,27893,27908,27915,27922,27929,27936,27943,27950,27957,27964,27980,27987],{"_key":27880,"_type":99,"children":27881,"markDefs":27885,"style":799},"qJVB7MS5yHYEga2U3kjjB",[27882],{"_type":103,"marks":27883,"text":27884},[],"Artificial intelligence (AI) and robots are digital technologies that already have and will continue to have a major influence on humanity’s progress and development. Their use has highlighted basic concerns about what companies should do with those systems, what hazards they pose, and how businesses might manage them. Moreover, everyone nowadays is wondering what are the moral principles behind AI. We try to answer this question in the following lines.",[],{"_key":27887,"_type":99,"children":27888,"markDefs":27892,"style":170},"kIddKKG6nuItMf2DluBad",[27889],{"_type":103,"marks":27890,"text":27891},[],"The hazard distribution of AI ethics principles and their meaning.",[],{"_key":27894,"_type":99,"children":27895,"markDefs":27905,"style":799},"0zmZK-qHrlDXCEWVCSI5Z",[27896,27899,27902],{"_type":103,"marks":27897,"text":27898},[],"Although AI ethics are based on concepts, the field has yet to coalesce around a single set of guiding principles. The business world should think about concepts that are better tailored to each domain and situation and strive toward more tangible manifestations that genuinely assist practitioners to lead their activities. However, if we have principles on one side, it, for sure, is necessary to have tools on the other. That is what one ",{"_type":103,"marks":27900,"text":12246},[27901],"mfkVDXUbAh-9lQf5qH_pA",{"_type":103,"marks":27903,"text":27904},[]," aimed to identify by classifying AI ethics tools and examining the ones already existing on the market.",[27906],{"_key":27901,"_type":173,"href":27907},"https://link.springer.com/article/10.1007/s43681-021-00084-x",{"_key":27909,"_type":99,"children":27910,"markDefs":27914,"style":799},"yV4d8n4aLAXEwpa52tGI9",[27911],{"_type":103,"marks":27912,"text":27913},[3055],"Key findings of the research acknowledged two main gaps. ",[],{"_key":27916,"_type":99,"children":27917,"level":230,"listItem":4889,"markDefs":27921,"style":107},"c4rxmWYtTCwRH-pa7ogAN",[27918],{"_type":103,"marks":27919,"text":27920},[],"To begin with, critical stakeholders, such as members of marginalized populations, are underrepresented in the use of AI ethical tools and their outcomes. ",[],{"_key":27923,"_type":99,"children":27924,"level":230,"listItem":4889,"markDefs":27928,"style":107},"toYQeOAmDfsuAd_XuZm1m",[27925],{"_type":103,"marks":27926,"text":27927},[],"Moreover, there are no external auditing tools for AI ethics, which is a barrier to the responsibility and integrity of companies that build AI systems. Nevertheless, the basis is set – there are at least some AI ethics tools already available in the business environment which need addressing improvements.",[],{"_key":27930,"_type":99,"children":27931,"markDefs":27935,"style":170},"6sg4YvMuqrA9izYCTvCqP",[27932],{"_type":103,"marks":27933,"text":27934},[],"AI Ethics and privacy.",[],{"_key":27937,"_type":99,"children":27938,"markDefs":27942,"style":799},"UasvKi53hbvc0XOh4YCJ-",[27939],{"_type":103,"marks":27940,"text":27941},[],"The arrival of AI raised privacy issues when compared to what humans were capable of previously. AI allows us to shine a light on every nook and cranny, every crevice, and sometimes even crevices we did not think to search for. Privacy, on the other hand, can serve as a paradigm for translating abstract ideas into actual implementations. Regulation to set actual rules that corporations must follow as it did for privacy, might work for AI ethics as well. On that note, before GDPR, the discussion of privacy was also abstract and unimaginable.",[],{"_key":27944,"_type":99,"children":27945,"markDefs":27949,"style":799},"Mfd1uiqvLKvsfOKkdzRfd",[27946],{"_type":103,"marks":27947,"text":27948},[],"What it succeeded in was that the introduction of GDPR generated a feeling of urgency, requiring enterprises to take real steps to comply. ",[],{"_key":27951,"_type":99,"children":27952,"markDefs":27956,"style":799},"nwRkldQpRSu5DREKd68B1",[27953],{"_type":103,"marks":27954,"text":27955},[],"This example illustrates the need for concrete regulations to keep AI Ethics steady and the same for all.",[],{"_key":27958,"_type":99,"children":27959,"markDefs":27963,"style":170},"ovIN94tEUheL7GicIB4VW",[27960],{"_type":103,"marks":27961,"text":27962},[],"The lack of well-defined AI ethics structures and the way businesses deploy AI tools.",[],{"_key":27965,"_type":99,"children":27966,"markDefs":27977,"style":799},"29xg6FibG7vTV3DYqEFag",[27967,27970,27974],{"_type":103,"marks":27968,"text":27969},[],"Various sets of legislation are already appearing in AI regulation. They impose different viewpoints and expectations from different regions of the world. As a result, we may end up in a chaos of regulatory systems that conflicts with ",{"_type":103,"marks":27971,"text":27973},[27972],"HDtaa4YJe1LAGVfsDG9Dh","human rights",{"_type":103,"marks":27975,"text":27976},[],". This will make it difficult for businesses to traverse the landscape and comply with the requirements, favoring those with greater resources. Furthermore, if the GDPR precedent is any indication, certain firms may withdraw from particular markets, limiting users’ options and customer satisfaction.",[27978],{"_key":27972,"_type":173,"href":27979},"https://cosmosthrace.com/is-ai-a-threat-to-human-rights/",{"_key":27981,"_type":99,"children":27982,"markDefs":27986,"style":799},"ee_6WdoNchkdtjOeck7bJ",[27983],{"_type":103,"marks":27984,"text":27985},[],"One approach to avoid this is for rules to come with their own set of open-source compliance tools. This would make it easier for numerous firms to compete while also guaranteeing regulatory compliance. ",[],{"_key":27988,"_type":99,"children":27989,"markDefs":27993,"style":799},"Ngi5AaRMfLJJWQAyAa01U",[27990],{"_type":103,"marks":27991,"text":27992},[],"All in all, businesses are still testing the waters of the ethics and moral principles behind AI. In a highly digitalized world, novelties emerge every day. However, nothing should go unnoticed, especially when we speak about AI technologies and the principles supporting them. The use of AI tools, the control of privacy, and the need for systemic restrictions are just the beginning of the issues that require strong measures. On grounds of business development, AI can give a significant competitive advantage. Nonetheless, by lacking any AI ethics, companies may misuse their benefits.",[],{"_type":17,"current":27871},[27996],{"_createdAt":13100,"_id":13101,"_rev":13102,"_type":8636,"_updatedAt":13103,"name":13104,"orderRank":12215,"uid":13105},{"_createdAt":27998,"_id":27999,"_rev":28000,"_system":28001,"_type":72,"_updatedAt":28004,"archived":126,"author":161,"category":28005,"date":27143,"description":28009,"image":161,"name":28018,"oldSlug":28019,"orderRank":28020,"reviewer":161,"sections":28021,"seo":161,"slug":28173,"tags":28174},"2026-01-15T16:12:28Z","c368752e-3296-4d70-96f5-ddb36a4a56d0","81Z7afF2ctpavAFo68Ybrf",{"base":28002},{"id":27999,"rev":28003},"ZfaOePOqVJD5r4KHzTVfsY","2026-01-28T08:07:44Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":28006,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":28008,"uid":30},{"base":28007},{"id":21,"rev":25},{"_type":17,"current":30},[28010],{"_key":28011,"_type":99,"children":28012,"markDefs":28017,"style":107},"d91b7ba4a73b",[28013],{"_key":28014,"_type":103,"marks":28015,"text":28016},"e9135a3f28b4",[],"In 2021 weekly cyber-attacks on corporate networks went up 50% compared to 2020 according to Check Point Research. That means over 900 attacks per organization per",[],"How can AI technology be applied to enhance Cyber Security","ai-and-cyber-security","0|1000pk:",[28022],{"_createdAt":28023,"_id":28024,"_key":28025,"_ref":28024,"_rev":28003,"_type":168,"_updatedAt":28023,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":28026,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:41:59Z","p8oLP-v8nYVpC_eyMR2Sd","lc516RrZXf3GqoztXuiIT",[28027,28043,28050,28057,28064,28071,28084,28097,28110,28117,28124,28131,28138,28145,28152,28159],{"_key":28028,"_type":99,"children":28029,"markDefs":28040,"style":799},"ea1GiyywQvwnzalYHBDE7",[28030,28033,28037],{"_type":103,"marks":28031,"text":28032},[],"In 2021 weekly cyber-attacks on corporate networks went up 50% compared to 2020 according to ",{"_type":103,"marks":28034,"text":28036},[28035],"tnPtAE95pKez3B9gSMswS","Check Point Research",{"_type":103,"marks":28038,"text":28039},[],". That means over 900 attacks per organization per week in the fourth quarter of 2021. What does this translate to? ",[28041],{"_key":28035,"_type":173,"href":28042},"https://blog.checkpoint.com/2022/01/10/check-point-research-cyber-attacks-increased-50-year-over-year/",{"_key":28044,"_type":99,"children":28045,"markDefs":28049,"style":799},"zyTS2Q-id2qdK3PYtdWmz",[28046],{"_type":103,"marks":28047,"text":28048},[],"Cyber Security is not a human-scale problem anymore. AI is and will be relied upon to handle this vast number of threats. ",[],{"_key":28051,"_type":99,"children":28052,"markDefs":28056,"style":799},"PdGqAj5zwCjnZe47GjIyf",[28053],{"_type":103,"marks":28054,"text":28055},[],"But how?",[],{"_key":28058,"_type":99,"children":28059,"markDefs":28063,"style":170},"9tgcYf8lClRTxGityOhY4",[28060],{"_type":103,"marks":28061,"text":28062},[],"The first task of AI and ML when it comes to Cyber Security is identifying and prioritizing Zero-Day malware threats.",[],{"_key":28065,"_type":99,"children":28066,"markDefs":28070,"style":799},"TR8ZHVngf4PEgChxsLfaM",[28067],{"_type":103,"marks":28068,"text":28069},[],"Apart from the high volume of threats, the sheer speed at which these threats adapt and change is a key issue for Cyber Security professionals. Malware keeps improving, and humans are unable to cope with the pressure. Even legacy software such as antivirus programs are unable to detect new threats, as by the time they are updated to account for a new piece of malware, there are already newer threats available. ",[],{"_key":28072,"_type":99,"children":28073,"markDefs":28083,"style":799},"0nai-T4bKut14co0_3vPM",[28074,28077,28080],{"_type":103,"marks":28075,"text":28076},[],"AI can combat this ever-evolving threat by using ",{"_type":103,"marks":28078,"text":28079},[3055],"deep learning algorithms",{"_type":103,"marks":28081,"text":28082},[]," in order to cross-check data and apply an ‘if this, then that’ approach to detecting problems. It looks at past occurrences and analyses current and predictive data to form a solid point of reference that detects malware. The more data and malware it goes over, the better it becomes at detecting new malware. This is done at speeds capable of outperforming the competition. ",[],{"_key":28085,"_type":99,"children":28086,"markDefs":28096,"style":799},"y7y8QMvlERidTIxTWv2hK",[28087,28090,28093],{"_type":103,"marks":28088,"text":28089},[],"On top of that ",{"_type":103,"marks":28091,"text":28092},[3055],"Ensemble learning",{"_type":103,"marks":28094,"text":28095},[]," is also used. This translates to using a layered approach, where multiple learning models are combined to create one that is more robust. This can boost detection rates and lower errors drastically. ",[],{"_key":28098,"_type":99,"children":28099,"markDefs":28109,"style":799},"VYTPGl6YWWtjLiYv79Zid",[28100,28103,28106],{"_type":103,"marks":28101,"text":28102},[],"Of course, all of the above is done under ",{"_type":103,"marks":28104,"text":28105},[3055],"human supervision",{"_type":103,"marks":28107,"text":28108},[],", where the Cyber Security team can focus on the AI and the real attacks, rather than on false positives.",[],{"_key":28111,"_type":99,"children":28112,"markDefs":28116,"style":170},"maNoDdzPmiWJ6vXSusYFv",[28113],{"_type":103,"marks":28114,"text":28115},[],"Endpoint security is becoming absolutely necessary.",[],{"_key":28118,"_type":99,"children":28119,"markDefs":28123,"style":799},"oJVC78Im7Ca9NA-zHLQXW",[28120],{"_type":103,"marks":28121,"text":28122},[],"Cyber-attacks haven’t only increased on corporate networks. Most people have spent a lot of time working from home in the last two years. This has led to the fast development of new malware and ransomware, capable of consistent attacks that businesses have to defend their employees at home from. ",[],{"_key":28125,"_type":99,"children":28126,"markDefs":28130,"style":799},"Jn8zfdCe0rLui_ytMqirT",[28127],{"_type":103,"marks":28128,"text":28129},[],"Aside from the increasing number of threats, and the ever-adaptiveness of them, business also face an increasing number of endpoint devices – from laptops, to computers, to phones, tablets, and wearable technology. Cyber threats target weaknesses based on user behavior and poor digital hygiene. ",[],{"_key":28132,"_type":99,"children":28133,"markDefs":28137,"style":799},"X_Gq9fZ09qwIEwralU1-d",[28134],{"_type":103,"marks":28135,"text":28136},[],"This variety of devices and threats can drain a Cyber Security team of their time and resources if they rely on standard practices. Meanwhile legacy software can cause potential disconnects, and zero-day exploits can targeted antivirus programs. As mentioned above, false positives also drain time and resources. ",[],{"_key":28139,"_type":99,"children":28140,"markDefs":28144,"style":799},"n66ntRqtufLa3l_CthzhC",[28141],{"_type":103,"marks":28142,"text":28143},[],"That is why AI and ML have become more and more in demand when it comes to endpoint security. The ability to examine every device, and monitor activity is crucial.",[],{"_key":28146,"_type":99,"children":28147,"markDefs":28151,"style":799},"eq3puT9jtWmBJhQ2gDhP1",[28148],{"_type":103,"marks":28149,"text":28150},[],"The information to be processed is too large to be examined by humans, but AI can do that easily.",[],{"_key":28153,"_type":99,"children":28154,"markDefs":28158,"style":799},"4PTYKKDKXDUGXjiRlBMBT",[28155],{"_type":103,"marks":28156,"text":28157},[],"In conclusion, just like any tool, AI and ML are best used when backed up by experience and knowledge. While AI technology won’t eliminate the need for a dedicated Cyber Security team, they will make its job much easier. ",[],{"_key":28160,"_type":99,"children":28161,"markDefs":28171,"style":799},"3aFDRRNZo5TnXw4fZPQ0X",[28162,28165,28168],{"_type":103,"marks":28163,"text":28164},[],"You can rely on ",{"_type":103,"marks":28166,"text":7898},[28167],"EWezHsZK92td-9ubGxpkD",{"_type":103,"marks":28169,"text":28170},[]," to give you the security that only AI can afford. With our hands on experience, we will support you on every step of the journey to security. ",[28172],{"_key":28167,"_type":173,"href":18723},{"_type":17,"current":28019},[28175,28176],{"_createdAt":13100,"_id":13101,"_rev":13102,"_type":8636,"_updatedAt":13103,"name":13104,"orderRank":12215,"uid":13105},{"_createdAt":10732,"_id":10733,"_rev":10734,"_type":8636,"_updatedAt":10735,"name":10736,"orderRank":10737,"uid":10738},{"_createdAt":28178,"_id":28179,"_rev":28180,"_system":28181,"_type":72,"_updatedAt":28184,"archived":126,"author":161,"category":28185,"date":27143,"description":28189,"image":161,"name":28198,"oldSlug":28199,"orderRank":28200,"reviewer":161,"sections":28201,"seo":161,"slug":28325,"tags":28326},"2026-01-15T16:06:18Z","d40ef0fc-5123-44b3-982e-865a816cc335","3x1HJiv3wwU7cYVoHt4ixU",{"base":28182},{"id":28179,"rev":28183},"ZfaOePOqVJD5r4KHzTUe7F","2026-01-28T08:15:30Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":28186,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":28188,"uid":54},{"base":28187},{"id":45,"rev":49},{"_type":17,"current":54},[28190],{"_key":28191,"_type":99,"children":28192,"markDefs":28197,"style":107},"5df4f3fe4927",[28193],{"_key":28194,"_type":103,"marks":28195,"text":28196},"3b992761a2c2",[],"The top 5 Applications of AI in Supply Chain: In recent years, supply chains have become considerably more challenging to manage due to the constant",[],"Top 5 Applications of AI in Supply Chain","top-5-applications-of-ai-in-supply-chain","0|1000mg:",[28202],{"_createdAt":28203,"_id":28204,"_key":28205,"_ref":28204,"_rev":28183,"_type":168,"_updatedAt":28203,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":28206,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:39:20Z","cNPVYdK8U8vIytUTkUSWH","JaYFXs4N14ohRL4F0PHJd",[28207,28214,28221,28228,28235,28242,28249,28256,28263,28270,28277,28284,28291,28297,28304],{"_key":28208,"_type":99,"children":28209,"markDefs":28213,"style":170},"qt755XcbMgr5wDh2YJhnz",[28210],{"_type":103,"marks":28211,"text":28212},[],"The top 5 Applications of AI in Supply Chain:",[],{"_key":28215,"_type":99,"children":28216,"markDefs":28220,"style":799},"X8Jrj0MVEZA4q9NeTlxQ4",[28217],{"_type":103,"marks":28218,"text":28219},[],"In recent years, supply chains have become considerably more challenging to manage due to the constant data flow. The accurate forecasting of demand has a vital role in a business from any category to continue running smoothly and achieve sales and profit growth. Experts have relied on traditional forecasting methods and tools to predict demand. Although these methods have helped them a lot in reducing demand-supply mismatch, there is still much room for improvement. Read the article and learn about the Top 5 applications of AI in Supply Chain.",[],{"_key":28222,"_type":99,"children":28223,"level":230,"listItem":231,"markDefs":28227,"style":107},"_icRp8gT9ROImejsP4Ggw",[28224],{"_type":103,"marks":28225,"text":28226},[],"1 Demand Forecasting",[],{"_key":28229,"_type":99,"children":28230,"markDefs":28234,"style":799},"2RsxfjXMVOn9qt-1opRJt",[28231],{"_type":103,"marks":28232,"text":28233},[],"Usually, businesses either underestimate or overestimate demand. This happens because the traditional models guess future demand based on historical data sales. However, these methods tend to reduce accuracy as past patterns change. They do not consider external factors that had an impact on previous demand, and they cannot apply them for future demands as well. On the contrary, AI-based solution looks at both external and internal factors to provide real-time data that can optimize processes. AI has the right set of tools and algorithms to predict complex and unpredictable for humans fluctuations in demand volumes and deliver accuracy. Those tools are proven to be effective in analyzing data quickly, providing timely guidance for forecasting seasonal demand. AI implementing will bring striking improvements in customer satisfaction, increase revenue, and reduce inventory expenses.",[],{"_key":28236,"_type":99,"children":28237,"level":230,"listItem":231,"markDefs":28241,"style":107},"xQoXFwe7pGLk9VUhKSCkI",[28238],{"_type":103,"marks":28239,"text":28240},[],"2 Slotting Adjustment",[],{"_key":28243,"_type":99,"children":28244,"markDefs":28248,"style":799},"CvIgPlGGzSMDhEK0m78lk",[28245],{"_type":103,"marks":28246,"text":28247},[],"One example where the traditional methods fail, and AI delivers the best results is dynamic slotting. Slotting is an example of a complex problem that requires considering many factors and has many goals, which sometimes even compete. Traditional slotting methods require a customized model, extensive engineering, and regular data update. Whereas AI minimizes the need for engineering work as well as eliminates manual warehouse mapping and data inputs. AI calculates the travel time required for slotting and self-adapts as conditions change over time. Thus, proper slotting has an impact on productivity, accuracy, order cycle time, and storage quantity and capacity.",[],{"_key":28250,"_type":99,"children":28251,"level":230,"listItem":231,"markDefs":28255,"style":107},"vmNZ_nJKFIe8aoovBrnje",[28252],{"_type":103,"marks":28253,"text":28254},[],"3 Staff planning and allocation",[],{"_key":28257,"_type":99,"children":28258,"markDefs":28262,"style":799},"TRp8DBM4hx9cTSiPLf39J",[28259],{"_type":103,"marks":28260,"text":28261},[],"AI can provide a solution to other problems in the supply chain as well. One of them is staff allocation, which is vital to ensure that orders will get out on time. To avoid overstaffing or understaffing, and lower overtime managers have to decide on how to allocate staff properly. Usually, managers take labor allocation decisions based on a shift in the volume of work, deadlines, and productivity. The predictions, however, are based on the experience and the skills of the manager, leaving room for error. AI can be used to predict staff requirements and to estimate the deadline for an order. Moreover, AI can determine the best way to fulfill an order, while avoiding delays, through simulations.",[],{"_key":28264,"_type":99,"children":28265,"level":230,"listItem":231,"markDefs":28269,"style":107},"TtnXcfPj6bpYfi1KBxV3t",[28266],{"_type":103,"marks":28267,"text":28268},[],"4 Labor Management",[],{"_key":28271,"_type":99,"children":28272,"markDefs":28276,"style":799},"CHIp_tFyqK_BCgyZ6AvdL",[28273],{"_type":103,"marks":28274,"text":28275},[],"Another important benefit of the AI approach is more effective performance management. Labor management systems and Engineered Labor Standards (ELS) have been used for years; however, AI has proven to be way more effective. ELS-based performance management requires intensive data collection and uses learning algorithms to estimate the required time for task completion. Meanwhile, the AI integration process is much easier, and the results are more accurate, as it automatically adjusts to changes. The AI solution is based on real-time performance data and considers multiple variables as the type of the task, starting location, quantity.",[],{"_key":28278,"_type":99,"children":28279,"level":230,"listItem":231,"markDefs":28283,"style":107},"07-ngGNEK4m7_uRy-MvKw",[28280],{"_type":103,"marks":28281,"text":28282},[],"5 Suppliers Relationship Management",[],{"_key":28285,"_type":99,"children":28286,"markDefs":28290,"style":799},"HL2QBWZsmFHBB0DAuNVQk",[28287],{"_type":103,"marks":28288,"text":28289},[],"Companies working in the supply chain heavily depend on their partners and suppliers to maintain working efficiently. To continue a smooth working process, they need the right technology that will combine both strategic and sustainable factors, while managing risks. For the big warehouses, the suppliers’ network is complex. Choosing the right supplier for a specific product can be challenging having into consideration possible discounts, delivery deadlines, and other factors. AI will help in managing the huge datasets about the suppliers, the products that provide, and their condition so that the company can manage its orders in the most optimal way in terms of cost, time and risk.",[],{"_key":28292,"_type":99,"children":28293,"markDefs":28296,"style":170},"O3sfuqWDwNl7GTX78bXFp",[28294],{"_type":103,"marks":28295,"text":22109},[],[],{"_key":28298,"_type":99,"children":28299,"markDefs":28303,"style":799},"5vheGrHKAJ_2zqJwKSgwR",[28300],{"_type":103,"marks":28301,"text":28302},[],"AI has already begun to change the supply chain industry by providing visibility into all aspects of the industry and delivering powerful optimization capabilities. AI-based solutions can make an intelligent supply chain that can produce higher quality products, by taking care of safety, managing inefficiencies, and decreasing risks.",[],{"_key":28305,"_type":99,"children":28306,"markDefs":28322,"style":799},"6YdqXRBoykZDQZ947-1Pa",[28307,28310,28313,28316,28319],{"_type":103,"marks":28308,"text":28309},[],"AI is going to become even more influential as time goes on. This is not just a solution for today, but a better future for your business. ",{"_type":103,"marks":28311,"text":7898},[28312],"diDXb-Enu69U-PHDDBxZt",{"_type":103,"marks":28314,"text":28315},[]," enables the integration of AI to the specific needs of your company while ensuring ease and haste in the delivery. ",{"_type":103,"marks":28317,"text":18707},[28318],"N6rtHfl1Q_s-sZqxBrJaQ",{"_type":103,"marks":28320,"text":28321},[]," to discuss how we can help.",[28323,28324],{"_key":28312,"_type":173,"href":19377},{"_key":28318,"_type":173,"href":19536},{"_type":17,"current":28199},[28327,28328,28329],{"_createdAt":24375,"_id":24376,"_rev":24377,"_type":8636,"_updatedAt":24378,"name":24379,"orderRank":13966,"uid":24380},{"_createdAt":27326,"_id":27327,"_rev":27328,"_type":8636,"_updatedAt":27329,"name":27330,"orderRank":14579,"uid":27331},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":28331,"_id":28332,"_rev":28333,"_system":28334,"_type":72,"_updatedAt":28337,"archived":126,"author":161,"category":28338,"date":28342,"description":28343,"image":161,"name":28352,"oldSlug":28353,"orderRank":28354,"reviewer":161,"sections":28355,"seo":161,"slug":28452,"tags":28453},"2026-01-15T16:03:33Z","5b4640cf-a864-46ec-89b6-ba752a8c45f1","3x1HJiv3wwU7cYVoHtIdgE",{"base":28335},{"id":28332,"rev":28336},"2oGVswEwQBfyYUvi7k5LaO","2026-01-28T08:36:17Z",{"_createdAt":44,"_id":45,"_rev":46,"_system":28339,"_type":12,"_updatedAt":50,"name":51,"orderRank":52,"slug":28341,"uid":54},{"base":28340},{"id":45,"rev":49},{"_type":17,"current":54},"2022-08-23",[28344],{"_key":28345,"_type":99,"children":28346,"markDefs":28351,"style":107},"f3de033b86b9",[28347],{"_key":28348,"_type":103,"marks":28349,"text":28350},"46f12ba44cc8",[],"Customer experience has always been crucial, no matter what industry you are in. In 2021, out of necessity because of the pandemic, the world has",[],"How chatbots deliver a better customer experience","how-chatbots-deliver-a-better-customer-experience","0|1000l4:",[28356],{"_createdAt":28357,"_id":28358,"_key":28359,"_ref":28358,"_rev":28336,"_type":168,"_updatedAt":28357,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":28360,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:37:31Z","lSPmruL707d9doymEc6mt","gAtuuxpZ2TmclrXU4Lc2o",[28361,28368,28375,28382,28389,28396,28403,28410,28417,28424,28431],{"_key":28362,"_type":99,"children":28363,"markDefs":28367,"style":799},"GvD4TjucpVNjoXUix67MD",[28364],{"_type":103,"marks":28365,"text":28366},[],"Customer experience has always been crucial, no matter what industry you are in. In 2021, out of necessity because of the pandemic, the world has fostered online environments that fully rely on customer experiences. So, how chatbots deliver a better customer experience?",[],{"_key":28369,"_type":99,"children":28370,"markDefs":28374,"style":170},"6Ng0ZAFTqSXvHb7pXFf6a",[28371],{"_type":103,"marks":28372,"text":28373},[],"So, why do customers value chatbots?",[],{"_key":28376,"_type":99,"children":28377,"markDefs":28381,"style":799},"qhmuUaBbN96N2Ou9WTCMj",[28378],{"_type":103,"marks":28379,"text":28380},[],"As we’ve said before. No beating around the bush from us. Chatbots are a key part of bettering customer experience these days. While some people desire human interaction when they face issues, most people desire a fast resolution to their questions even more. Chatbots, using NLP tech, have proven to be the saving grace of customers and businesses during the pandemic, when online traffic was higher than ever. ",[],{"_key":28383,"_type":99,"children":28384,"markDefs":28388,"style":170},"tohSsHQrT55G7N5xLLJLU",[28385],{"_type":103,"marks":28386,"text":28387},[],"Got to go fast!",[],{"_key":28390,"_type":99,"children":28391,"markDefs":28395,"style":799},"XsYhFSWYsOpYJsBn681pG",[28392],{"_type":103,"marks":28393,"text":28394},[],"That is one of the most valued benefits of a Chatbot when it comes to customer experience. 37% of those asked, stated that Getting a quick answer in an emergency is why they use a chatbot. For companies with a massive customer base, or with limited resources, hiring enough staff to provide timely answers to customers is nigh-impossible. Chatbots, however, are the solution to bettering customer experience in this area. ",[],{"_key":28397,"_type":99,"children":28398,"markDefs":28402,"style":799},"5cmZ2D7VdvTsoEydEXADc",[28399],{"_type":103,"marks":28400,"text":28401},[],"That is another thing live agents can’t reliably provide – instant answers around the clock.",[],{"_key":28404,"_type":99,"children":28405,"markDefs":28409,"style":170},"Wsju9Wy9T0VF4pUg767la",[28406],{"_type":103,"marks":28407,"text":28408},[],"How important is 24/7 Support?",[],{"_key":28411,"_type":99,"children":28412,"markDefs":28416,"style":799},"QA5yAANTQPMNkhwxrjlxy",[28413],{"_type":103,"marks":28414,"text":28415},[],"Around-the-clock agent support is expensive for a business, thus harder to get if you’re a customer. But once we get through the easy questions, once the issue seems to be more complex than what AI can handle, a chatbot can seamlessly escalate to a live agent, without wasting time. The chatbot can easily provide the agent with all information gathered from the customer before, during and after their query. This leads to a quicker issue resolution, and to a better customer experience due to cherishing the customer’s time.",[],{"_key":28418,"_type":99,"children":28419,"markDefs":28423,"style":170},"d03Lh1FpuPu4pY-REmNBe",[28420],{"_type":103,"marks":28421,"text":28422},[],"Why customer experience matters:",[],{"_key":28425,"_type":99,"children":28426,"markDefs":28430,"style":799},"T1Zf7spZLsMV4PGtiienM",[28427],{"_type":103,"marks":28428,"text":28429},[],"Companies are truly missing out on sales by virtue of not having live chat support and chatbots. So, are you still wondering how chatbots deliver a better customer experience?",[],{"_key":28432,"_type":99,"children":28433,"markDefs":28449,"style":799},"ANqS1wEWCUJPUIg5r7Zf8",[28434,28437,28440,28443,28446],{"_type":103,"marks":28435,"text":28436},[],"This is where ",{"_type":103,"marks":28438,"text":7898},[28439],"wpD9XcJPLW8eJxmBEUoiY",{"_type":103,"marks":28441,"text":28442},[]," can help, with our timely integration and fine-tuning of AI. Chatbots are an extension of what we already have ample experience in developing. ",{"_type":103,"marks":28444,"text":18707},[28445],"v8AJn7gkBu3HJlocsnPHk",{"_type":103,"marks":28447,"text":28448},[]," to find out more. ",[28450,28451],{"_key":28439,"_type":173,"href":18723},{"_key":28445,"_type":173,"href":19536},{"_type":17,"current":28353},[28454,28457,28458],{"_createdAt":21691,"_id":21692,"_rev":21693,"_system":28455,"_type":8636,"_updatedAt":21697,"name":21698,"orderRank":13162,"uid":21699},{"base":28456},{"id":21692,"rev":21696},{"_createdAt":21701,"_id":21702,"_rev":21703,"_type":8636,"_updatedAt":21704,"name":21705,"orderRank":12869,"uid":21706},{"_createdAt":16589,"_id":16590,"_rev":16591,"_type":8636,"_updatedAt":16592,"name":16593,"orderRank":16594,"uid":16595},{"_createdAt":28460,"_id":28461,"_rev":28462,"_system":28463,"_type":72,"_updatedAt":28466,"archived":126,"author":161,"category":28467,"date":28342,"description":28471,"image":161,"name":28480,"oldSlug":28481,"orderRank":28482,"reviewer":161,"sections":28483,"seo":161,"slug":28605,"tags":28606},"2026-01-15T16:00:00Z","c854a8cd-2470-4bd8-b072-5829ffcfb992","3x1HJiv3wwU7cYVoHstgAr",{"base":28464},{"id":28461,"rev":28465},"ZfaOePOqVJD5r4KHzTTNEg","2026-01-28T08:05:49Z",{"_createdAt":20,"_id":21,"_rev":22,"_system":28468,"_type":12,"_updatedAt":26,"name":27,"orderRank":28,"slug":28470,"uid":30},{"base":28469},{"id":21,"rev":25},{"_type":17,"current":30},[28472],{"_key":28473,"_type":99,"children":28474,"markDefs":28479,"style":107},"45d43c2432ac",[28475],{"_key":28476,"_type":103,"marks":28477,"text":28478},"30b244dc4019",[],"As technology continues to evolve, it’s having an increasing influence over our everyday activities, both professional and personal. Disruptive technologies such as Artificial Intelligence",[],"What is the relationship between AI and 5G?","what-is-the-relationship-between-ai-and-5g","0|1000jc:",[28484],{"_createdAt":28485,"_id":28486,"_key":28487,"_ref":28486,"_rev":28465,"_type":168,"_updatedAt":28485,"background":161,"bckg":161,"button":161,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":28488,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-22T18:34:59Z","Y_m_bP9dHx0rzyC18mDwK","RLpqrC804KUMY5xDnF4rE",[28489,28496,28511,28518,28525,28532,28539,28546,28553,28565,28574,28581,28588],{"_key":28490,"_type":99,"children":28491,"markDefs":28495,"style":170},"nT0RtX1o5VSyspoHChIdm",[28492],{"_type":103,"marks":28493,"text":28494},[],"Introduction:",[],{"_key":28497,"_type":99,"children":28498,"markDefs":28509,"style":799},"_2L3pTCRu_GrJqyHoVKWu",[28499,28502,28506],{"_type":103,"marks":28500,"text":28501},[],"As technology continues to evolve, it’s having an increasing influence over our everyday activities, both professional and personal. Disruptive technologies such as ",{"_type":103,"marks":28503,"text":28505},[28504],"CUlS1bHiUt70P_OKNLMT_","Artificial Intelligence (AI)",{"_type":103,"marks":28507,"text":28508},[]," and 5G are beginning to gain wider acceptance amongst businesses. Even activities that are now just seen as part of normal life, like using phone assistants such as Siri, rely more and more on those technologies. So, let’s explore what is the relationship between AI and 5G.",[28510],{"_key":28504,"_type":173,"href":27673},{"_key":28512,"_type":99,"children":28513,"markDefs":28517,"style":170},"k8LyqsCjNUoHH6lF0-gPs",[28514],{"_type":103,"marks":28515,"text":28516},[],"How are AI and 5G related?",[],{"_key":28519,"_type":99,"children":28520,"markDefs":28524,"style":799},"yYNvbcnOucuuhrnoM52Th",[28521],{"_type":103,"marks":28522,"text":28523},[],"The development of AI models requires large amounts of data. At the same time, 5G technology can collect all that data at a very high speed, from a huge number of devices and with a very low latency. However, collecting data at such a pace is of no use if we cannot analyze it. That’s where AI comes in.",[],{"_key":28526,"_type":99,"children":28527,"markDefs":28531,"style":799},"Ci4Zcmk-ng-pwXNWnpPji",[28528],{"_type":103,"marks":28529,"text":28530},[],"To put it into perspective, 5G provides the infrastructure and massive amounts of data required for successful AI, while AI, driven by advances in machine learning, provides the ability to make sense of the chaos and complexity of 5G.",[],{"_key":28533,"_type":99,"children":28534,"markDefs":28538,"style":799},"F3JYhxuAk4dQEFV23ErFq",[28535],{"_type":103,"marks":28536,"text":28537},[],"In a nutshell, AI and 5G are not only related to each other, they are dependent on each other to succeed and play a role in everyday life.",[],{"_key":28540,"_type":99,"children":28541,"markDefs":28545,"style":170},"uueWKAuljXr9g2BTuu14n",[28542],{"_type":103,"marks":28543,"text":28544},[],"The benefits of the relationship between AI and 5G",[],{"_key":28547,"_type":99,"children":28548,"markDefs":28552,"style":799},"E9qJiyhhcuOETAROMUcwz",[28549],{"_type":103,"marks":28550,"text":28551},[],"So, how can businesses and people make practical use of these advanced technologies? One example is that smart, AI-based devices can be installed almost anywhere and linked to each other. They can then collect data, analyze it and make near real-time decisions. To put this into a perspective, consider the following industries:",[],{"_key":28554,"_type":99,"children":28555,"level":230,"listItem":4889,"markDefs":28564,"style":107},"AjKo0_BWjnUi71ptJnrYR",[28556,28558,28561],{"_type":103,"marks":28557,"text":22148},[3055],{"_type":103,"marks":28559,"text":28560},[],":",{"_type":103,"marks":28562,"text":28563},[],"We are at the edge of the fourth industrial revolution and 5G and AI play big part in its development. Sensors can be installed in machines that form part of assembly lines. This allows vast amounts of real-time data to be extracted through 5G technology. Those sensors are then connected to each other and allow AI technology to make fast decisions based on real-time data. 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Usually one mini project takes between 3-6 months to complete as it depends on the scope of each project.",[],{"_key":30840,"_type":99,"children":30841,"markDefs":30846,"style":107},"5a90e0fecf65",[30842],{"_key":30843,"_type":103,"marks":30844,"text":30845},"6780e5e138db",[],"In terms of technology Python is the main language used for programming. Everything is developed in the Linux environment; MATLAB algorithms are used and Data structures are defined and developed in C++. We felt comfortable working with those tools and languages as we already had an experience in all of them.",[],{"_key":30848,"_type":99,"children":30849,"markDefs":30854,"style":107},"fa37b28d52bc",[30850],{"_key":30851,"_type":103,"marks":30852,"text":30853},"f1bb298cbbbf",[],"Each sub-project is divided into three phases. First it starts with the preparation of the User Interface and the data structures; After that, the main logic is executed. 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",[],{"_key":33909,"_type":99,"children":33910,"markDefs":33914,"style":107},"2e7d69f5723e",[33911],{"_key":33904,"_type":103,"marks":33912,"text":33913},[],"Companies typically migrate from Snowflake when they need better AI/ML support or want to reduce costs, and from legacy warehouses (Teradata, Oracle) when they need modern performance and cloud scalability. 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",[],{"_key":33944,"_type":99,"children":33945,"markDefs":33949,"style":107},"346d75e25f6f",[33946],{"_key":33939,"_type":103,"marks":33947,"text":33948},[],"You see concrete results, e.g. churn prediction model saved €240K in Q1 by retaining 15% more customers, rather than vague \"improved accuracy\" claims. ",[],{"_key":33951,"_type":99,"children":33952,"markDefs":33956,"style":107},"30b41fde906b",[33953],{"_key":33939,"_type":103,"marks":33954,"text":33955},[],"Monthly reports compare AI predictions to actual outcomes in business terms, showing exactly which models deliver value and which need adjustment. 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",[],{"_key":34001,"_type":99,"children":34002,"markDefs":34006,"style":107},"dff9c19c6bf5",[34003],{"_key":33996,"_type":103,"marks":34004,"text":34005},[],"Your business users see simple explanations (\"this customer is high-risk because payment history shows 3 late payments in 6 months\"), while your data scientists can access full technical details including feature importance, SHAP values, and model architecture. ",[],{"_key":34008,"_type":99,"children":34009,"markDefs":34013,"style":107},"cf47c23bcf3a",[34010],{"_key":33996,"_type":103,"marks":34011,"text":34012},[],"We also document when AI recommendations should be trusted versus when human judgment is needed, ensuring your teams understand both the capabilities and limitations of each model.",[],"How do you make AI models explainable and trustworthy?",{"_key":34016,"description":34017,"title":34040},"992978306b8a",[34018,34026,34033],{"_key":34019,"_type":99,"children":34020,"markDefs":34025,"style":107},"3cd4d785c9f6",[34021],{"_key":34022,"_type":103,"marks":34023,"text":34024},"cbca085289f2",[],"We build your team's independence through knowledge transfer at every phase, not consultant dependency. ",[],{"_key":34027,"_type":99,"children":34028,"markDefs":34032,"style":107},"97f9b2403f84",[34029],{"_key":34022,"_type":103,"marks":34030,"text":34031},[],"Your data scientists receive hands-on MLOps training during development, your IT teams get deployment guides they can follow independently, and your business users learn to interpret AI outputs through role-specific workshops. ",[],{"_key":34034,"_type":99,"children":34035,"markDefs":34039,"style":107},"9b98b1c66752",[34036],{"_key":34022,"_type":103,"marks":34037,"text":34038},[],"We provide 3-6 months of hands-on support as your teams gain confidence, then offer tiered support options from basic monitoring (monthly health checks) to full managed services.",[],"What happens after implementation? Will we become dependent on consultants?",{"_key":34042,"description":34043,"title":34066},"716d7b972585",[34044,34052,34059],{"_key":34045,"_type":99,"children":34046,"markDefs":34051,"style":107},"a5c2ee62a1ba",[34047],{"_key":34048,"_type":103,"marks":34049,"text":34050},"c069be713376",[],"Enterprise AI projects typically run 4-8 months from discovery to production, and we strongly recommend starting with a 6-12 week pilot that validates one critical use case before full commitment. ",[],{"_key":34053,"_type":99,"children":34054,"markDefs":34058,"style":107},"dc3e1adca2c1",[34055],{"_key":34048,"_type":103,"marks":34056,"text":34057},[],"The pilot proves your approach works with real data, demonstrates measurable business value to executives, and identifies any data quality or integration issues early, preventing the \"big bang\" failures where organizations invest heavily only to discover fundamental problems during deployment. ",[],{"_key":34060,"_type":99,"children":34061,"markDefs":34065,"style":107},"7296f646a7c9",[34062],{"_key":34048,"_type":103,"marks":34063,"text":34064},[],"Weekly progress dashboards show exactly what's built, tested, and production-ready at each phase, so you're never wondering where the project stands.",[],"How long does AI implementation take, and can we start with a pilot?",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},{"_type":10536,"ogImage":161,"title":17494},{"_type":17,"current":31634},{"_createdAt":31639,"_id":31640,"_rev":31641,"_system":34071,"_type":10505,"_updatedAt":31645,"name":31646,"orderRank":52,"sections":34073,"seo":35531,"slug":35532},{"base":34072},{"id":31640,"rev":31644},[34074,34088,35528],{"_createdAt":34075,"_id":31650,"_key":31649,"_ref":31650,"_rev":34076,"_type":23200,"_updatedAt":34077,"background":161,"bckg":161,"button":34078,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":161,"image":161,"images":161,"links":161,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"subtitle":34079,"team":161,"thumbnail":161,"title":31646,"titleLevel":182},"2026-01-14T13:04:16Z","BV7Sm6F4lThNfRDi4hSQ4Y","2026-02-09T13:48:35Z",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[34080],{"_key":34081,"_type":99,"children":34082,"markDefs":34087,"style":107},"oWRwVdnFw0WxZrGH9nL3d",[34083],{"_key":34084,"_type":103,"marks":34085,"text":34086},"fe-nnoIxiB-d1baZS2dyY",[],"The protection of all personal data, in particular the strict respect of confidentiality of customers’ and employees’ data and compliance with the data protection laws applicable, is not only a legal requirement for us. Providing data protection is the basis for strong relationships with customers, business partners and employees. It is, therefore, a matter of great importance for us to protect confidential personal data from any unauthorized access. We draw the attention to this topic in the following Privacy Policy.",[],{"_createdAt":34089,"_id":31653,"_key":31652,"_ref":31653,"_rev":34090,"_system":34091,"_type":168,"_updatedAt":34094,"afterTextLevel":170,"background":161,"bckg":161,"bigTextLevel":171,"button":34095,"cards":161,"caseStudies":161,"category":161,"certificates":161,"content":34096,"descriptionLevel":799,"image":161,"images":161,"links":161,"panelTitle":31646,"redirect":161,"sections":161,"selectedArticles":161,"selectedTestimonials":161,"team":161,"thumbnail":161},"2026-01-14T13:01:23Z","YjNvQx4tqfWKwO39Ej0H9b",{"base":34092},{"id":31653,"rev":34093},"82W3GKXTFwGqAwh8HC8PzF","2026-01-29T09:25:39Z",{"_type":173,"customName":125,"customUrl":125,"newTab":125,"page":161},[34097,34105,34113,34121,34129,34137,34145,34153,34161,34169,34177,34185,34193,34201,34209,34217,34225,34233,34241,34249,34257,34265,34273,34281,34289,34297,34305,34313,34321,34329,34337,34345,34353,34361,34369,34377,34385,34393,34401,34409,34417,34425,34433,34441,34449,34457,34465,34473,34481,34489,34497,34505,34513,34521,34529,34537,34545,34553,34561,34569,34577,34585,34593,34601,34609,34617,34625,34633,34641,34649,34657,34664,34672,34680,34688,34696,34704,34712,34720,34728,34736,34744,34752,34760,34768,34776,34784,34792,34800,34808,34816,34824,34832,34840,34848,34856,34864,34872,34880,34888,34896,34904,34912,34920,34928,34936,34944,34952,34960,34968,34976,34984,34992,35000,35008,35016,35024,35032,35040,35048,35056,35064,35072,35080,35088,35096,35104,35112,35120,35128,35136,35144,35152,35160,35168,35176,35184,35192,35200,35208,35216,35228,35236,35244,35252,35260,35272,35280,35288,35296,35308,35322,35336,35348,35356,35364,35372,35380,35388,35396,35408,35416,35424,35432,35440,35448,35456,35464,35472,35480,35488,35496,35504,35512,35520],{"_key":34098,"_type":99,"children":34099,"markDefs":34104,"style":182},"4abe2beb15c0",[34100],{"_key":34101,"_type":103,"marks":34102,"text":34103},"edc46e5a59b4",[],"I. INTRODUCTION",[],{"_key":34106,"_type":99,"children":34107,"markDefs":34112,"style":107},"052f161f1aaf",[34108],{"_key":34109,"_type":103,"marks":34110,"text":34111},"74ef6e03b856",[],"(1) COSMOS THRACE Ltd. (“Cosmos”) is a commercial company registered in the Commercial Register at the Registry Agency with UIC 205813928 , with registered office and address of management: Sofia, Chernorizetz Hrabar str. №3 , 3rd flr.\n(2) COSMOS THRACE is a controller of personal data within the meaning of Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation).",[],{"_key":34114,"_type":99,"children":34115,"markDefs":34120,"style":107},"2627d0f780b7",[34116],{"_key":34117,"_type":103,"marks":34118,"text":34119},"a18c81accb37",[],"(3) While carrying out its commercial activity COSMOS THRACE shall process personal data in strict compliance with the provisions of the General Regulation on Data Protection and the Personal Data Protection Act (PDPA).\n(4) In fulfillment of its commitment to ensure full compliance with the legislation of the European Union (EU) and the Republic of Bulgaria regarding the processing of personal data, COSMOS THRACE adopts this Privacy Policy, which is applicable to all processing activities performed by COSMOS THRACE of personal data.",[],{"_key":34122,"_type":99,"children":34123,"markDefs":34128,"style":107},"c921dc50e525",[34124],{"_key":34125,"_type":103,"marks":34126,"text":34127},"df4a9af1ca6b",[],"(5) This policy applies to all personal data processed by COSMOS THRACE , including personal data of customers, employees, suppliers, subcontractors, partners.",[],{"_key":34130,"_type":99,"children":34131,"markDefs":34136,"style":107},"3630cb289587",[34132],{"_key":34133,"_type":103,"marks":34134,"text":34135},"eb1c962f562a",[],"(6) This privacy policy is mandatory and should be observed by all suppliers, subcontractors, partners, employees working with or for COSMOS THRACE , as well as by third parties who have or may have access to COSMOS THRACE personal data.",[],{"_key":34138,"_type":99,"children":34139,"markDefs":34144,"style":182},"e6e27253400f",[34140],{"_key":34141,"_type":103,"marks":34142,"text":34143},"54ae647b8b9c",[],"II. DEFINITIONS",[],{"_key":34146,"_type":99,"children":34147,"markDefs":34152,"style":107},"f2dff8083a59",[34148],{"_key":34149,"_type":103,"marks":34150,"text":34151},"5fd0d06606d9",[],"For the purposes of the General Data Protection Regulation and for the purposes of this Privacy Policy, the following terms have the following meaning:",[],{"_key":34154,"_type":99,"children":34155,"markDefs":34160,"style":107},"c58280f0e1a8",[34156],{"_key":34157,"_type":103,"marks":34158,"text":34159},"c9563130b302",[],"1. Personal data – any information related to an identified natural person or an identifiable natural person (data subject); an identifiable natural person is an identifiable person, directly or indirectly, in particular by an identifier such as name, identification number, location data, online identifier or one or more features specific to the natural, the physiological, genetic, mental, intellectual, economic, cultural or social identity of that individual;",[],{"_key":34162,"_type":99,"children":34163,"markDefs":34168,"style":107},"fd27a587c04f",[34164],{"_key":34165,"_type":103,"marks":34166,"text":34167},"26ed2c8b62a9",[],"2. Special categories of personal data – personal data revealing racial or ethnic origin, political views, religious or philosophical beliefs or trade union membership, as well as the processing of genetic data, biometric data for the sole purpose of identifying an individual, health data condition or data on the sexual life or sexual orientation of the individual;",[],{"_key":34170,"_type":99,"children":34171,"markDefs":34176,"style":107},"b21268438b86",[34172],{"_key":34173,"_type":103,"marks":34174,"text":34175},"eeacf25b9173",[],"3. Processing – an operation or set of operations performed with personal data or a set of personal data by automatic or other means such as collection, recording, organizing, structuring, storing, adapting or modifying, retrieving, consulting, using, disclosing, transmitting, distributing or any other way in which data is made available, arranged or combined, restricted, deleted or destroyed;",[],{"_key":34178,"_type":99,"children":34179,"markDefs":34184,"style":107},"1601786edf48",[34180],{"_key":34181,"_type":103,"marks":34182,"text":34183},"70b655dc2402",[],"4. Administrator – a natural or legal person, public body, agency or other structure, which alone or jointly with others determines the purposes and means for the processing of personal data; where the purposes and means of such processing are determined by EU law or the law of a Member State, the controller or the specific criteria for determining it may be laid down in the Union’s law or in the law of a Member State;",[],{"_key":34186,"_type":99,"children":34187,"markDefs":34192,"style":107},"c231b1499bcb",[34188],{"_key":34189,"_type":103,"marks":34190,"text":34191},"11963ed94752",[],"5. Personal data processor – a natural or legal person, public authority, agency or other structure that processes personal data on behalf of the controller;",[],{"_key":34194,"_type":99,"children":34195,"markDefs":34200,"style":107},"1ec602bcd921",[34196],{"_key":34197,"_type":103,"marks":34198,"text":34199},"59ff244606d9",[],"6. Data subject – a natural person who has been identified or who can be identified on the basis of certain information;",[],{"_key":34202,"_type":99,"children":34203,"markDefs":34208,"style":107},"c6f3196accdd",[34204],{"_key":34205,"_type":103,"marks":34206,"text":34207},"fe6c4962487c",[],"7. Recipient – a natural or legal person, public authority, agency or other entity to which personal data are disclosed, whether a third party or not. However, public authorities that may receive personal data in the context of a specific investigation in accordance with EU or Member State law shall not be considered as recipients; the processing of such data by those public authorities complies with the applicable data protection rules in accordance with the purposes of the processing;",[],{"_key":34210,"_type":99,"children":34211,"markDefs":34216,"style":107},"c5b51faddc46",[34212],{"_key":34213,"_type":103,"marks":34214,"text":34215},"838b3882449a",[],"8. Third party – natural or legal person, public authority, agency or other authority other than the data subject, the controller, the processor and the persons who, under the direct supervision of the controller or the processor, have the right to process personal data;",[],{"_key":34218,"_type":99,"children":34219,"markDefs":34224,"style":107},"c2ec42d52d90",[34220],{"_key":34221,"_type":103,"marks":34222,"text":34223},"ec9a1511ea25",[],"9. Violation of the security of personal data – means a breach of security that results in accidental or unlawful destruction, loss, alteration, unauthorized disclosure or access to personal data that is transmitted, stored or otherwise processed.",[],{"_key":34226,"_type":99,"children":34227,"markDefs":34232,"style":107},"3677469a06bd",[34228],{"_key":34229,"_type":103,"marks":34230,"text":34231},"87277acb1a56",[],"10. Supervisory body means the Commission for Personal Data Protection in the Republic of Bulgaria.",[],{"_key":34234,"_type":99,"children":34235,"markDefs":34240,"style":182},"3d992a804c08",[34236],{"_key":34237,"_type":103,"marks":34238,"text":34239},"d7da94435d49",[],"III. PRINCIPLES RELATED TO THE PROCESSING OF PERSONAL DATA",[],{"_key":34242,"_type":99,"children":34243,"markDefs":34248,"style":107},"b092c13a7bcb",[34244],{"_key":34245,"_type":103,"marks":34246,"text":34247},"d3486e8d3d05",[],"COSMOS THRACE processes personal data in accordance with the principles related to the processing of personal data, regulated in Art. 5 of the General Data Protection Regulation, namely:",[],{"_key":34250,"_type":99,"children":34251,"markDefs":34256,"style":107},"6a46e65a99ed",[34252],{"_key":34253,"_type":103,"marks":34254,"text":34255},"59b3bbe97315",[],"1. Compliance, Fairness and Transparency\nCOSMOS THRACE processes personal data in compliance with the mandatory provisions of the General Data Protection Regulation and the LPPD, sincerely and openly.",[],{"_key":34258,"_type":99,"children":34259,"markDefs":34264,"style":107},"f06878116c23",[34260],{"_key":34261,"_type":103,"marks":34262,"text":34263},"181022f6ca16",[],"2. Limited Data Collection\nCOSMOS THRACE processes personal data only for specific, explicitly stated and lawful purposes and does not further process them in a manner incompatible with these purposes.",[],{"_key":34266,"_type":99,"children":34267,"markDefs":34272,"style":107},"10ba29da180f",[34268],{"_key":34269,"_type":103,"marks":34270,"text":34271},"867b36c65b23",[],"3. Minimizing the Personal Data Used\nCOSMOS THRACE processes personal data, limited as necessary in connection with the purposes for which they are processed. COSMOS THRACE collects and processes only the minimum necessary personal data of individuals which:\n• are provided by law;\n• are needed to perform a contract;\n• are needed to fulfill the purposes for which they are collected.",[],{"_key":34274,"_type":99,"children":34275,"markDefs":34280,"style":107},"8f66ba1d23de",[34276],{"_key":34277,"_type":103,"marks":34278,"text":34279},"ea67a66a7153",[],"4. Collected personal data shall be processed for other purposes only with the consent of the persons\nIn all cases where it is necessary for the collected and processed personal data of individuals to be used for purposes other than the primary ones, COSMOS THRACE notifies the relevant individuals, seeks their consent and proceeds to process their personal data for other purposes only after their explicit consent.",[],{"_key":34282,"_type":99,"children":34283,"markDefs":34288,"style":107},"91aa9abb842f",[34284],{"_key":34285,"_type":103,"marks":34286,"text":34287},"b37f9dfe8375",[],"5. Accuracy and Timeliness\nThe personal data stored by COSMOS THRACE shall be kept accurate and up-to-date, and all reasonable measures shall be taken to ensure the timely correction of inaccurate personal data.",[],{"_key":34290,"_type":99,"children":34291,"markDefs":34296,"style":107},"d109cb1d0101",[34292],{"_key":34293,"_type":103,"marks":34294,"text":34295},"b80482edc753",[],"6. Storage restriction\nCOSMOS THRACE stores personal data in a form that allows the identification of the data subject for a period not longer than necessary for the purposes which the personal data are processed for. Personal data may be stored for longer periods insofar as they will be processed exclusively for archiving purposes in the public interest, for scientific or historical research or for statistical purposes in accordance with Article 89 (1), provided that the appropriate technical and organizational measures provided for in this Regulation in order to guarantee the rights and freedoms of the data subject (“storage restriction”).",[],{"_key":34298,"_type":99,"children":34299,"markDefs":34304,"style":107},"66cf065e6f95",[34300],{"_key":34301,"_type":103,"marks":34302,"text":34303},"38a27c31f295",[],"7. Integrity and confidentiality\nCOSMOS THRACE processes personal data in a way that ensures an appropriate level of security, including protection against unauthorized or unlawful processing and against accidental loss, destruction or damage, by applying appropriate technical or organizational measures.",[],{"_key":34306,"_type":99,"children":34307,"markDefs":34312,"style":107},"5f2fa8707e94",[34308],{"_key":34309,"_type":103,"marks":34310,"text":34311},"db3dc7fc2c09",[],"8. Accountability\nCOSMOS THRACE is responsible and able to prove that it complies with its obligations in relation to the processing of personal data.",[],{"_key":34314,"_type":99,"children":34315,"markDefs":34320,"style":182},"efbaca135c05",[34316],{"_key":34317,"_type":103,"marks":34318,"text":34319},"370546fdbc01",[],"IV. CATEGORIES OF DATA SUBJECTS AND CATEGORIES OF PERSONAL DATA",[],{"_key":34322,"_type":99,"children":34323,"markDefs":34328,"style":107},"7d9a154926b8",[34324],{"_key":34325,"_type":103,"marks":34326,"text":34327},"2354aba2449e",[],"COSMOS THRACE processes personal data of individuals who visit the company website. The following categories of personal data may be processed:",[],{"_key":34330,"_type":99,"children":34331,"markDefs":34336,"style":107},"514c0a52f05a",[34332],{"_key":34333,"_type":103,"marks":34334,"text":34335},"5c3d974520bd",[],"• Technical data: IP address, browser type, device information, operating system; • Behavioral data: pages visited, time on site, referring website; • Identification data: where available through third-party matching services, professional email address and company information.",[],{"_key":34338,"_type":99,"children":34339,"markDefs":34344,"style":107},"b7174da62fcf",[34340],{"_key":34341,"_type":103,"marks":34342,"text":34343},"117eee436372",[],"In the event that COSMOS THRACE decides to process data of data subjects for marketing purposes, it shall take the measures necessary to obtain prior informed consent from the data subject.",[],{"_key":34346,"_type":99,"children":34347,"markDefs":34352,"style":107},"951873b8e8c5",[34348],{"_key":34349,"_type":103,"marks":34350,"text":34351},"6785d20febaf",[],"2. Job candidates\n• Ordinary personal data: Information contained in the CV of the candidate, such as names of the person, contact details (telephone number and e-mail), copies of documents for professional and educational qualification, etc.",[],{"_key":34354,"_type":99,"children":34355,"markDefs":34360,"style":107},"4cbadf6f2fd3",[34356],{"_key":34357,"_type":103,"marks":34358,"text":34359},"8103d06f1dda",[],"3. Staff\nCOSMOS THRACE collects the following categories of personal data from employees:\n• Ordinary personal data: names, PIN, passport data, education and qualifications, profession, length of service, remuneration, bank account data and others;",[],{"_key":34362,"_type":99,"children":34363,"markDefs":34368,"style":107},"06d3aca3b1bc",[34364],{"_key":34365,"_type":103,"marks":34366,"text":34367},"4ded1c117285",[],"• Special category of personal data: health status information contained in sick leaves, documents certifying permanent incapacity for work and / or other documents required by the applicable legislation for the respective position or in order to exercise specific rights of the employee.",[],{"_key":34370,"_type":99,"children":34371,"markDefs":34376,"style":107},"0385337c7081",[34372],{"_key":34373,"_type":103,"marks":34374,"text":34375},"b07cd8f3d52d",[],"In the general case, COSMOS THRACE does not process personal data of employees on the basis of consent. However, in certain situations, consent may be required where it is required by the applicable law, including for the processing of a specific category of personal data.",[],{"_key":34378,"_type":99,"children":34379,"markDefs":34384,"style":182},"f284c89f9727",[34380],{"_key":34381,"_type":103,"marks":34382,"text":34383},"18f9f560714e",[],"V. OBLIGATION FOR LAWFUL AND CONSCIENTIAL PROCESSING OF PERSONAL DATA",[],{"_key":34386,"_type":99,"children":34387,"markDefs":34392,"style":107},"6323232d90c7",[34388],{"_key":34389,"_type":103,"marks":34390,"text":34391},"6404201d8197",[],"(1) COSMOS THRACE establishes the grounds for processing the personal data under Art. 6 (1) of the General Data Protection Regulation:",[],{"_key":34394,"_type":99,"children":34395,"markDefs":34400,"style":107},"24b9e8cfdc4e",[34396],{"_key":34397,"_type":103,"marks":34398,"text":34399},"5d149173e06f",[],"1. The data subject has given consent to the processing of his/her personal data for one or more specific purposes.\n2. Processing is necessary for the performance of a contract to which the data subject is party or in order to take steps at the request of the data subject prior to entering into a contract.",[],{"_key":34402,"_type":99,"children":34403,"markDefs":34408,"style":107},"535833feef70",[34404],{"_key":34405,"_type":103,"marks":34406,"text":34407},"368756a726fb",[],"3. Processing is necessary for compliance with a legal obligation to which the controller is subject.",[],{"_key":34410,"_type":99,"children":34411,"markDefs":34416,"style":107},"8818835bf041",[34412],{"_key":34413,"_type":103,"marks":34414,"text":34415},"10a99724d726",[],"4. Processing is necessary in order to protect the vital interests of the data subject or of another natural person.",[],{"_key":34418,"_type":99,"children":34419,"markDefs":34424,"style":107},"db7d3af0c02b",[34420],{"_key":34421,"_type":103,"marks":34422,"text":34423},"f9e54cbfeece",[],"5. Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.",[],{"_key":34426,"_type":99,"children":34427,"markDefs":34432,"style":107},"4e462ef54c6c",[34428],{"_key":34429,"_type":103,"marks":34430,"text":34431},"ad2f35b9a5bc",[],"6. Processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child.",[],{"_key":34434,"_type":99,"children":34435,"markDefs":34440,"style":107},"6ae7c593ab2d",[34436],{"_key":34437,"_type":103,"marks":34438,"text":34439},"bf2d9cf2bb43",[],"(2) COSMOS THRACE performs only activities for processing personal data for which there is any of the grounds under Art. 6 (1) of the General Data Protection Regulation.",[],{"_key":34442,"_type":99,"children":34443,"markDefs":34448,"style":182},"79ed0f7fd264",[34444],{"_key":34445,"_type":103,"marks":34446,"text":34447},"aa1ab12234fa",[],"VI. OBLIGATION TO PROCESS PERSONAL DATA FOR SPECIFIC PURPOSES",[],{"_key":34450,"_type":99,"children":34451,"markDefs":34456,"style":107},"78e93cc812d0",[34452],{"_key":34453,"_type":103,"marks":34454,"text":34455},"5e4741e4ceb8",[],"(1) The processing of personal data shall be carried out in fulfillment of the legal obligations of COSMOS THRACE , as well as in fulfillment of contractual obligations undertaken by COSMOS THRACE or on the basis of informed consent given by the client.",[],{"_key":34458,"_type":99,"children":34459,"markDefs":34464,"style":107},"534a5d6cf566",[34460],{"_key":34461,"_type":103,"marks":34462,"text":34463},"9b8d6a00a456",[],"(2) In carrying out its commercial activity COSMOS THRACE shall collect and use categories of personal data, indicated in the register of the activities for processing of personal data under art. 30 (1) of the General Data Protection Regulation (Appendix No.1). COSMOS THRACE receives personal data directly from the data subject (for example, when completing validated sample documents or correspondence via email, telephone or other means of communication) or from other sources (e.g. from partners, subcontractors, payment service providers, etc.).",[],{"_key":34466,"_type":99,"children":34467,"markDefs":34472,"style":107},"7e229021e12a",[34468],{"_key":34469,"_type":103,"marks":34470,"text":34471},"0c03463a3f3e",[],"(3) COSMOS THRACE shall process personal data only for specific and explicitly indicated purposes, indicated in the register of the activities for processing of personal data under Art. 30 (1) of the General Data Protection Regulation, namely:",[],{"_key":34474,"_type":99,"children":34475,"markDefs":34480,"style":107},"33c8b12713b9",[34476],{"_key":34477,"_type":103,"marks":34478,"text":34479},"9a73c7e41fb2",[],"1. For implementation of the services offered by COSMOS THRACE ;\n2. for client registration and respectively for reporting;\n3. in order to fulfill a contract, which has been concluded or which is in the process of conclusion with a client of COSMOS THRACE , as well as for the conclusion or execution of a labour agreement with employees of COSMOS THRACE;",[],{"_key":34482,"_type":99,"children":34483,"markDefs":34488,"style":107},"42e821493a3a",[34484],{"_key":34485,"_type":103,"marks":34486,"text":34487},"7d1d7697fa50",[],"4. when this is necessary for the protection of the legitimate interests of COSMOS THRACE or third parties, provided that the legitimate interests and fundamental rights and freedoms of the data subject do not take precedence over these legitimate interests;\n5. for up-to-date contact information with the data subject;\n6. for providing information, including marketing communication through the channels chosen by the client (e.g. e-mail or telephone).\n7. for website analytics and visitor identification to improve our services and provide relevant business communications;\n8. for targeted marketing communications to identified website visitors who may benefit from COSMOS THRACE services.",[],{"_key":34490,"_type":99,"children":34491,"markDefs":34496,"style":107},"c635c94cbcba",[34492],{"_key":34493,"_type":103,"marks":34494,"text":34495},"eb11350add6a",[],"(4) In case the data of the subject have to be used for a purpose incompatible with the original one, COSMOS THRACE shall notify him/her in due time and explain to him/her what is the legal basis, which allows the data to be used for this new purpose as well.\n(5) COSMOS THRACE provides the data subjects with the opportunity to choose whether to share their personal data with the company. In case the data subject objects to the processing of the personal data by COSMOS THRACE , the company respects this choice in accordance with its legal obligations. The objection may mean that COSMOS THRACE will not be able to carry out the activities necessary to achieve the objectives described above. It may also mean that the subject may not be able to use the services and products offered by COSMOS THRACE if he/she does not provide him/her with personal information about himself or if, after the data subject has provided this information, he/she objects to the processing. by COSMOS THRACE .",[],{"_key":34498,"_type":99,"children":34499,"markDefs":34504,"style":107},"d034e7f3b040",[34500],{"_key":34501,"_type":103,"marks":34502,"text":34503},"2f8377003681",[],"(6) The following applies to COSMOS THRACE ’s employee data",[],{"_key":34506,"_type":99,"children":34507,"markDefs":34512,"style":107},"fcdf7131f9d5",[34508],{"_key":34509,"_type":103,"marks":34510,"text":34511},"792a18e96780",[],"1. Personal data of employees can be processed within the context of the employment relationship, when necessary for meeting hiring decisions or in the aftermath of such, for delivering upon or termination of the employment contract, for exercising or satisfying the rights and obligations of representatives of contractors and employees. Personal data of these data subjects can be processed in favor of crime investigations only when there is ground to believe the investigated crime has taken place during the time of ongoing employment relationship and in case that the lawful right of the data subject for his/hers own data not to be processed does not prevail and more specific the type and scope of data processing are not disproportionate to the underlying reasons for investigation.",[],{"_key":34514,"_type":99,"children":34515,"markDefs":34520,"style":107},"189c6199658c",[34516],{"_key":34517,"_type":103,"marks":34518,"text":34519},"665a602ae580",[],"2. The Company sets in place the needed mechanisms for ensuring compliance with the principles of personal data processing, in line with the General Regulation, covered in section III.",[],{"_key":34522,"_type":99,"children":34523,"markDefs":34528,"style":107},"831f0da40c78",[34524],{"_key":34525,"_type":103,"marks":34526,"text":34527},"dd43fd4de419",[],"3. These rules also apply when personal data, including special categories of personal data, of employees are processed without participating or intended to be part of a document registration system.",[],{"_key":34530,"_type":99,"children":34531,"markDefs":34536,"style":107},"9226c9b31f48",[34532],{"_key":34533,"_type":103,"marks":34534,"text":34535},"1a7aa91db570",[],"4. In this context, the persons who will be considered as employees are also persons employed for the purposes of vocational training (trainees).\n5. Data processing is necessary to comply with the legal obligations of Cosmos Thrace. The processing of personal data for employees is also admissible where national law requires, prescribes or authorizes data processing. The nature and scope of the data processing must be necessary for legally required data processing activities and comply with the relevant legal provisions. Personal data may be shared with different categories of recipients. For example, COSMOS THRACE provides personal data to the National Revenue Agency, the National Social Security Institute, the Executive Agency “General Labor Inspectorate”, competent law enforcement, law enforcement agencies, as well as other government agencies and institutions.",[],{"_key":34538,"_type":99,"children":34539,"markDefs":34544,"style":182},"c04ec3f01f10",[34540],{"_key":34541,"_type":103,"marks":34542,"text":34543},"6789822951ec",[],"VII. OBLIGATION TO NOTIFY THE DATA SUBJECT",[],{"_key":34546,"_type":99,"children":34547,"markDefs":34552,"style":107},"3c3f2d75e0e3",[34548],{"_key":34549,"_type":103,"marks":34550,"text":34551},"83b8c6aafeb8",[],"(1) In fulfillment of its obligations under art. 12, 13 and 14 of the General Data Protection Regulation COSMOS THRACE provides the data subject with comprehensible and easily accessible information about the personal data that it processes.",[],{"_key":34554,"_type":99,"children":34555,"markDefs":34560,"style":107},"9e2e284b3364",[34556],{"_key":34557,"_type":103,"marks":34558,"text":34559},"b62e6348fb5f",[],"1. In the event that COSMOS THRACE receives personal data directly from the data subject, the data subject shall be informed of the confidentiality in an appropriate form containing clear, simple and comprehensible language and including the following information:\na) the data identifying COSMOS THRACE and the contact details of COSMOS THRACE and, where applicable, those of the COSMOS THRACE representative;",[],{"_key":34562,"_type":99,"children":34563,"markDefs":34568,"style":107},"0df6a1f89c00",[34564],{"_key":34565,"_type":103,"marks":34566,"text":34567},"cb380c4f11a0",[],"b) the contact details of the Data Protection Officer, where applicable;\nc) the purposes of the processing which the personal data are intended for and the legal basis for the processing;\nd) where the processing is carried out on the basis of Article 6, para. 1, item f) of the General Data Protection Regulation (legitimate interests of COSMOS THRACE or a third party), the legitimate interests pursued by COSMOS THRACE or a third party;",[],{"_key":34570,"_type":99,"children":34571,"markDefs":34576,"style":107},"d6db478d28e8",[34572],{"_key":34573,"_type":103,"marks":34574,"text":34575},"7cacdc7f51cd",[],"e) the recipients or categories of recipients of the personal data, if any;\nf) where applicable, the intention of COSMOS THRACE to transfer personal data to a third country or to an international organization, as well as the presence or absence of a decision of the European Commission (EC) on the adequate level of protection or in case of data transfer 46 or 47, or Article 49 (1), para. 2 of the General Data Protection Regulation, a reference to the appropriate or applicable safeguards and the means of obtaining a copy thereof or information where available;",[],{"_key":34578,"_type":99,"children":34579,"markDefs":34584,"style":107},"c3adf1dea026",[34580],{"_key":34581,"_type":103,"marks":34582,"text":34583},"734b636793eb",[],"g) the period which the personal data will be stored for and, if not possible, the criteria used to determine that period;\nh) the existence of a right to request COSMOS THRACE access to personal data, to correct or delete personal data or to restrict the processing of personal data relating to the data subject, or a right to object to the processing, as well as the right to the portability of the data;",[],{"_key":34586,"_type":99,"children":34587,"markDefs":34592,"style":107},"16593c3ff520",[34588],{"_key":34589,"_type":103,"marks":34590,"text":34591},"2c1fcb770145",[],"i) where the processing is based on the consent of the data subject, the existence of a right of withdrawal of consent at any time, without prejudice to the lawfulness of the processing based on consent before it is withdrawn;",[],{"_key":34594,"_type":99,"children":34595,"markDefs":34600,"style":107},"7e89ef4a0e28",[34596],{"_key":34597,"_type":103,"marks":34598,"text":34599},"45bc845b56f6",[],"j) the right to appeal to the Commission for Personal Data Protection (CPDP);\ne) whether the provision of personal data is a mandatory or contractual requirement or a requirement necessary for the conclusion of a contract, and whether the data subject is obliged to provide personal data and the possible consequences if such data is not provided;",[],{"_key":34602,"_type":99,"children":34603,"markDefs":34608,"style":107},"10ed240c8f69",[34604],{"_key":34605,"_type":103,"marks":34606,"text":34607},"fa1086e39891",[],"2. In the event that COSMOS THRACE receives personal data from sources other than the data subject, the data subject shall be informed of the confidentiality in an appropriate form containing clear, simple and comprehensible language and including the information referred to in the previous point, as and information on the relevant categories of personal data, as well as the source of the personal data and, if applicable, whether the data are from a publicly available source. The privacy notice shall be brought to the attention of the data subject within a reasonable time after receipt of the personal data, but no later than 1 month or upon contacting the data subject at the latest or disclosing the personal data to another recipient for the first time.",[],{"_key":34610,"_type":99,"children":34611,"markDefs":34616,"style":182},"5d10d222cd76",[34612],{"_key":34613,"_type":103,"marks":34614,"text":34615},"dcee4d097e4b",[],"VIII. OBLIGATION FOR ADEQUATE, RELEVANT AND RESTRICTED PROCESSING OF PERSONAL DATA",[],{"_key":34618,"_type":99,"children":34619,"markDefs":34624,"style":107},"c8485671342b",[34620],{"_key":34621,"_type":103,"marks":34622,"text":34623},"7a7c2ca9ab89",[],"COSMOS THRACE collects personal data within the limits of what is necessary for the purpose of processing, brought to the knowledge of the data subject.",[],{"_key":34626,"_type":99,"children":34627,"markDefs":34632,"style":182},"08305b5dfb6b",[34628],{"_key":34629,"_type":103,"marks":34630,"text":34631},"d1e5804ce8aa",[],"IX. OBLIGATION TO PROCESS ACCURATE AND UPDATED PERSONAL DATA",[],{"_key":34634,"_type":99,"children":34635,"markDefs":34640,"style":107},"d5ea9b5a3259",[34636],{"_key":34637,"_type":103,"marks":34638,"text":34639},"fdf8e4d62cfb",[],"(1) COSMOS THRACE collects accurate personal data and ensures its timely updating.\n(2) Upon receipt of personal data, the employees of COSMOS THRACE , engaged in the process of collection of personal data, shall check the accuracy of the personal data provided to COSMOS THRACE .\n(3) The personal data stored by COSMOS THRACE shall be reviewed periodically.\n(4) COSMOS THRACE has adopted rules for processing the applications for correction of personal data by the data subject (Appendix No. 2).",[],{"_key":34642,"_type":99,"children":34643,"markDefs":34648,"style":107},"4a33e6374958",[34644],{"_key":34645,"_type":103,"marks":34646,"text":34647},"2a80d25c1a1d",[],"(5) All suppliers, subcontractors, partners, workers and employees who work with or for COSMOS THRACE , as well as third parties who provide personal data to COSMOS THRACE , shall be obliged to notify of any change in the personal data provided by them.",[],{"_key":34650,"_type":99,"children":34651,"markDefs":34656,"style":182},"8ab69de28501",[34652],{"_key":34653,"_type":103,"marks":34654,"text":34655},"c906ca437696",[],"X. PROVISION OF PERSONAL DATA OF THE ENTITY TO THIRD PARTIES",[],{"_key":34658,"_type":99,"children":34659,"markDefs":34663,"style":107},"88eb456f0ddd",[34660],{"_key":34653,"_type":103,"marks":34661,"text":34662},[],"(1) Personal data may be shared with different categories of recipients. For example, in fulfilling legal obligations of the administrator, personal data may be provided to the National Revenue Agency, the National Social Security Institute, the Executive Agency “General Labor Inspectorate”, competent law enforcement, law enforcement agencies, as well as other government agencies and institutions.",[],{"_key":34665,"_type":99,"children":34666,"markDefs":34671,"style":107},"f42776db7e56",[34667],{"_key":34668,"_type":103,"marks":34669,"text":34670},"23c638cc8a27",[],"(2) COSMOS THRACE transfers data to other natural / legal persons who provide a certain type of goods or services to COSMOS THRACE , including services for information maintenance and security of IT systems, accounting services, archive and legal services and others. In such cases, COSMOS THRACE shall enter into a written agreement with the specific service provider that has provided sufficient guarantees for the application of appropriate technical and organizational measures in such a way that the processing complies with the requirements of Regulation (EU) 2016/679 and ensures protection of the rights of data subjects.",[],{"_key":34673,"_type":99,"children":34674,"markDefs":34679,"style":107},"607869b2e62e",[34675],{"_key":34676,"_type":103,"marks":34677,"text":34678},"a40cbdcb9ceb",[],"(3) COSMOS THRACE maintains partnerships with other independent controllers of personal data. In connection with this partnership, it is possible for the parties to share certain data with each other. In such cases, COSMOS THRACE shall inform the data subjects in an appropriate manner about these categories of recipients, as well as conclude an additional agreement with the respective independent controller, thus, ensuring the confidentiality of the personal data shared.",[],{"_key":34681,"_type":99,"children":34682,"markDefs":34687,"style":107},"f8bc389a1a14",[34683],{"_key":34684,"_type":103,"marks":34685,"text":34686},"24e8ccc9209a",[],"(4) If there is the figure of joint administrators between COSMOS THRACE and a third-party administrator, they shall define in a transparent manner their respective responsibilities for the implementation of the obligations under Regulation (EU) 2016/679 by mutual agreement.",[],{"_key":34689,"_type":99,"children":34690,"markDefs":34695,"style":107},"1675df9d0ae2",[34691],{"_key":34692,"_type":103,"marks":34693,"text":34694},"7e1f2e697437",[],"(5) COSMOS THRACE uses website tracking and visitor identification services, including RB2B (Retention.com), which may process visitor data on behalf of COSMOS THRACE. These service providers act as data processors under Article 28 of Regulation (EU) 2016/679 and appropriate data processing agreements are in place.",[],{"_key":34697,"_type":99,"children":34698,"markDefs":34703,"style":170},"ece7f812a4fd",[34699],{"_key":34700,"_type":103,"marks":34701,"text":34702},"217fc7e35da9",[],"XI. INTERNATIONAL TRANSFER OF PERSONAL DATA – TRANSMISSION OF PERSONAL DATA TO THIRD COUNTRIES OUTSIDE THE EU AND THE EEA",[],{"_key":34705,"_type":99,"children":34706,"markDefs":34711,"style":107},"82ad3af15405",[34707],{"_key":34708,"_type":103,"marks":34709,"text":34710},"e29323a0a3ab",[],"(1) COSMOS THRACE may transfer personal data to third countries outside the European Union and the European Economic Area only in compliance with the requirements of Regulation (EU) 2016/679 and in particular those set out in Chapter V thereof.\n(2) The transfer shall be made on the basis of a decision of the European Commission regarding the adequate level of protection provided by the third party in question. In the absence of such a decision by the European Commission, the transfer to a third party can only take place if there are adequate safeguards and provided that the data subjects’ rights and effective remedies are in place. Appropriate safeguards are standard data protection clauses included in personal data processing agreements concluded between COSMOS THRACE and the third party concerned.",[],{"_key":34713,"_type":99,"children":34714,"markDefs":34719,"style":107},"7248f20b2930",[34715],{"_key":34716,"_type":103,"marks":34717,"text":34718},"6218c7bc474e",[],"(3) Alternatively, the transfer of personal data to a third party may take place after the explicit consent of the data subject or where there are other grounds referred to in Article 49 (1) of Regulation (EU) 2016/679.",[],{"_key":34721,"_type":99,"children":34722,"markDefs":34727,"style":182},"f7a51cff230d",[34723],{"_key":34724,"_type":103,"marks":34725,"text":34726},"6106928c9ad3",[],"XII. OBLIGATION TO LIMIT THE STORAGE OF PERSONAL DATA",[],{"_key":34729,"_type":99,"children":34730,"markDefs":34735,"style":107},"a0aa0fca2072",[34731],{"_key":34732,"_type":103,"marks":34733,"text":34734},"54f5d0968a25",[],"(1) COSMOS THRACE shall store personal data only for a period not longer than necessary for the purposes for which the personal data are processed.",[],{"_key":34737,"_type":99,"children":34738,"markDefs":34743,"style":107},"171fca7d3f7f",[34739],{"_key":34740,"_type":103,"marks":34741,"text":34742},"e13b57eda768",[],"(2) After the expiration of the term of storage COSMOS THRACE shall ensure their proper destruction or deletion in accordance with an established procedure.\n(3) Terms for storage of personal data in COSMOS THRACE",[],{"_key":34745,"_type":99,"children":34746,"markDefs":34751,"style":107},"646cd52db381",[34747],{"_key":34748,"_type":103,"marks":34749,"text":34750},"0fcddef13d45",[],"1. The personal data of employees contained in the employment insurance documentation are stored for a period of 50 (fifty) years in accordance with the National Archives Fund Act, the Accounting Act, the Social Security Code and the Tax Insurance Procedure Code;",[],{"_key":34753,"_type":99,"children":34754,"markDefs":34759,"style":107},"0a168be4ff44",[34755],{"_key":34756,"_type":103,"marks":34757,"text":34758},"b82db07cebd3",[],"2. Personal data of job applicants who have not been approved for appointment in COSMOS THRACE are stored for a period not longer than 6 (six) months from the end of the procedure, after which they are returned to the person or destroyed in an appropriate manner. Personal data may be stored for a long period for the purpose of submitting job offers only with the consent of the job applicant;",[],{"_key":34761,"_type":99,"children":34762,"markDefs":34767,"style":107},"71c454dd6473",[34763],{"_key":34764,"_type":103,"marks":34765,"text":34766},"d7008aa0ec90",[],"3. The records from the technical means for video surveillance are stored for 2 (two) months from their preparation;",[],{"_key":34769,"_type":99,"children":34770,"markDefs":34775,"style":107},"3dcfbbe9e324",[34771],{"_key":34772,"_type":103,"marks":34773,"text":34774},"c91f887b9289",[],"4. Personal data contained in accounting documents are stored within the time limits under Article 12 of the Accounting Act.",[],{"_key":34777,"_type":99,"children":34778,"markDefs":34783,"style":107},"fd9e89e9944a",[34779],{"_key":34780,"_type":103,"marks":34781,"text":34782},"fb62f67f2a69",[],"5. Along with these basic deadlines, COSMOS THRACE has established its rules for determining the term for storage and procedure for destruction of personal data (Аppendix No. 3).",[],{"_key":34785,"_type":99,"children":34786,"markDefs":34791,"style":182},"f857436f74db",[34787],{"_key":34788,"_type":103,"marks":34789,"text":34790},"4739f16d968c",[],"XIII. OBLIGATION TO PROCESS PERSONAL DATA IN ACCORDANCE WITH THE RIGHTS OF THE DATA SUBJECT",[],{"_key":34793,"_type":99,"children":34794,"markDefs":34799,"style":107},"c73b8e73a47f",[34795],{"_key":34796,"_type":103,"marks":34797,"text":34798},"ca84ba54909e",[],"COSMOS THRACE processes personal data, ensuring the exercise of the rights of the data subject, namely:",[],{"_key":34801,"_type":99,"children":34802,"markDefs":34807,"style":107},"702cd6943bcd",[34803],{"_key":34804,"_type":103,"marks":34805,"text":34806},"987ee69c5c74",[],"1. right to information about his/her personal data stored by COSMOS THRACE and receipt of a copy of his/her personal data stored (right of access);",[],{"_key":34809,"_type":99,"children":34810,"markDefs":34815,"style":107},"f1538b7af3db",[34811],{"_key":34812,"_type":103,"marks":34813,"text":34814},"284d356a14c3",[],"2. right to correction of his/her personal data, if the same are inaccurate or out of date;",[],{"_key":34817,"_type":99,"children":34818,"markDefs":34823,"style":107},"9b31ee68a44c",[34819],{"_key":34820,"_type":103,"marks":34821,"text":34822},"27ecbcfbf6e3",[],"3. the right to have his/her personal data deleted, if applicable (right to be forgotten);",[],{"_key":34825,"_type":99,"children":34826,"markDefs":34831,"style":107},"3b7ce355154f",[34827],{"_key":34828,"_type":103,"marks":34829,"text":34830},"3c01c0670492",[],"4. right to limit the processing of his/her personal data;\n5. the right to withdraw the consent for processing of his/her personal data, if applicable;",[],{"_key":34833,"_type":99,"children":34834,"markDefs":34839,"style":107},"b65dcb4dc0f0",[34835],{"_key":34836,"_type":103,"marks":34837,"text":34838},"7f24fb96c05e",[],"6. right of portability of his/her personal data (to receive them or to be transferred to another personal data controller in a structured, widely used and machine-readable format), if applicable;",[],{"_key":34841,"_type":99,"children":34842,"markDefs":34847,"style":107},"ebd581c8dbdd",[34843],{"_key":34844,"_type":103,"marks":34845,"text":34846},"e55919f40663",[],"7. the right of his/her personal data not to be the subject of automatically taken decisions, which would affect him/her to a significant degree, without the possibility for human intervention;\n8. right to object to the processing of his/her personal data, if applicable;\n9. right to appeal against the processing of his/her personal data before the Commission for Personal Data Protection (CPDP) – Sofia, 1592, Blvd. “Prof. Tsvetan Lazarov” No 2 or at www.cpdp.bg.",[],{"_key":34849,"_type":99,"children":34850,"markDefs":34855,"style":182},"367fe04a0048",[34851],{"_key":34852,"_type":103,"marks":34853,"text":34854},"2923ac188e60",[],"XIV. OBLIGATION FOR REPORTING ON THE PROCESSING OF PERSONAL DATA",[],{"_key":34857,"_type":99,"children":34858,"markDefs":34863,"style":107},"e1bfbc55e91f",[34859],{"_key":34860,"_type":103,"marks":34861,"text":34862},"58e1b9fe1519",[],"(1) COSMOS THRACE shall be liable and shall be able to prove that it complies with its obligations in connection with the processing of personal data.\n(2) In its capacity of administrator of personal data COSMOS THRACE has created and maintains a register of the activities for processing personal data under Art. 30 (1) of the General Data Protection Regulation, according to an approved model, which contains the following information:\n1. activity for processing of the personal data;\n2. purpose of the processing of the personal data;\n3. grounds for processing the personal data;",[],{"_key":34865,"_type":99,"children":34866,"markDefs":34871,"style":107},"36ab99325565",[34867],{"_key":34868,"_type":103,"marks":34869,"text":34870},"ffd07f4087ba",[],"4. category of personal data subjects;",[],{"_key":34873,"_type":99,"children":34874,"markDefs":34879,"style":107},"dc3a8e2134c6",[34875],{"_key":34876,"_type":103,"marks":34877,"text":34878},"b738fb3c9480",[],"5. categories of personal data;",[],{"_key":34881,"_type":99,"children":34882,"markDefs":34887,"style":107},"4a3f41cc0e2a",[34883],{"_key":34884,"_type":103,"marks":34885,"text":34886},"61b2156a2b90",[],"6. source of the personal data;\n7. term of storage of the personal data;\n8. recipients of personal data;\n9. automated decision-making / profiling;",[],{"_key":34889,"_type":99,"children":34890,"markDefs":34895,"style":107},"355146bb6590",[34891],{"_key":34892,"_type":103,"marks":34893,"text":34894},"40d51a3f4550",[],"10. organizational and technical measures for protection;\n11. name of the state or the international organization upon transfer of personal data;\n12. guarantees for transfer of personal data to third countries or international organizations;",[],{"_key":34897,"_type":99,"children":34898,"markDefs":34903,"style":107},"0009e6788740",[34899],{"_key":34900,"_type":103,"marks":34901,"text":34902},"6975cfe6f3bc",[],"13. joint administrators;\n14. processing personal data.\n(3) When necessary COSMOS THRACE shall carry out an assessment of the impact on the protection of the personal data, taking into account all the circumstances, related to the activities for processing of personal data.\n(4) Where, as a result of the personal data protection impact assessment, it is clear that COSMOS THRACE will start processing personal data which, due to a high risk, could cause harm to data subjects, the decision whether or not to continue processing should to be submitted for review by the Data Protection Officer.",[],{"_key":34905,"_type":99,"children":34906,"markDefs":34911,"style":107},"e216775f7e68",[34907],{"_key":34908,"_type":103,"marks":34909,"text":34910},"7fc3d844d12c",[],"(5) In case the data protection officer has serious concerns about the potential damage or danger, or about the quantity of the respective data, the issue should be referred to the CPDP.",[],{"_key":34913,"_type":99,"children":34914,"markDefs":34919,"style":107},"d481eec3f824",[34915],{"_key":34916,"_type":103,"marks":34917,"text":34918},"8a190a517794",[],"(6) COSMOS THRACE shall prove the fulfillment of its obligations in connection with the processing of personal data by documenting the main processes of personal data processing, adoption and application of rules and procedures for personal data processing, as well as by joining codes of conduct, implementation of appropriate technical and organizational measures, adoption of personal data protection techniques at the design stage and default personal data protection, assessment of the impact on personal data protection, etc.",[],{"_key":34921,"_type":99,"children":34922,"markDefs":34927,"style":182},"bcd3a00c4e41",[34923],{"_key":34924,"_type":103,"marks":34925,"text":34926},"fe5c94342c3d",[],"XV. OBLIGATION TO GUARANTEE SECURITY IN THE PROCESSING OF PERSONAL DATA",[],{"_key":34929,"_type":99,"children":34930,"markDefs":34935,"style":107},"101993976599",[34931],{"_key":34932,"_type":103,"marks":34933,"text":34934},"181fd5253268",[],"(1) COSMOS THRACE is aware of the risks associated with the processing of certain categories of personal data.\n(2) In determining the appropriateness of the processing, COSMOS THRACE shall consider the extent of any damage or loss that may be caused to the data subject if a security breach occurs, as well as any probable damage to COSMOS THRACE ‘s reputation, including any loss of customer trust.",[],{"_key":34937,"_type":99,"children":34938,"markDefs":34943,"style":107},"0964729b0eac",[34939],{"_key":34940,"_type":103,"marks":34941,"text":34942},"13d74d26decd",[],"1. In assessing appropriate technical measures to ensure security in the processing of personal data, COSMOS THRACE shall analyze the following circumstances:\na) password protection provided;",[],{"_key":34945,"_type":99,"children":34946,"markDefs":34951,"style":107},"00694b8fa4be",[34947],{"_key":34948,"_type":103,"marks":34949,"text":34950},"20d0577f9357",[],"b) the existence of automatic locking of idle workstations in the network;\nc) removal of access rights for USB and other removable storage media;\nd) antivirus software and firewalls;\ne) access rights;\nf) the protection of devices leaving the premises of the organization, such as laptops and mobile phones;",[],{"_key":34953,"_type":99,"children":34954,"markDefs":34959,"style":107},"c239e1487dad",[34955],{"_key":34956,"_type":103,"marks":34957,"text":34958},"eb8e48ca90b1",[],"g) the security of local and wide area networks;",[],{"_key":34961,"_type":99,"children":34962,"markDefs":34967,"style":107},"3fbb2a6af413",[34963],{"_key":34964,"_type":103,"marks":34965,"text":34966},"724666b747e5",[],"h) confidentiality enhancement technologies, such as pseudonymization and anonymization;",[],{"_key":34969,"_type":99,"children":34970,"markDefs":34975,"style":107},"2f88f8d9c0c0",[34971],{"_key":34972,"_type":103,"marks":34973,"text":34974},"fc670c250c3b",[],"i) identification of appropriate international security standards.\n2. In assessing the appropriate organizational measures to ensure security in the processing of personal data, COSMOS THRACE shall take into account:",[],{"_key":34977,"_type":99,"children":34978,"markDefs":34983,"style":107},"d0047707e027",[34979],{"_key":34980,"_type":103,"marks":34981,"text":34982},"b2585e5a78ee",[],"a) appropriate training for COSMOS THRACE staff;",[],{"_key":34985,"_type":99,"children":34986,"markDefs":34991,"style":107},"a7e0bb408c85",[34987],{"_key":34988,"_type":103,"marks":34989,"text":34990},"ade4ca1fa4f1",[],"b) guarantees of the reliability of COSMOS THRACE staff (e.g. recommendations);\nc) the inclusion of obligations regarding the protection of personal data in the employment contracts of the employees of COSMOS THRACE ;\nd) the provision of disciplinary sanctions for the employees of COSMOS THRACE for violations in the processing of personal data;",[],{"_key":34993,"_type":99,"children":34994,"markDefs":34999,"style":107},"7b7ee9897b28",[34995],{"_key":34996,"_type":103,"marks":34997,"text":34998},"fb2fb601b730",[],"e) regular inspections of COSMOS THRACE staff to comply with the security standards relevant;",[],{"_key":35001,"_type":99,"children":35002,"markDefs":35007,"style":107},"8a15d7599079",[35003],{"_key":35004,"_type":103,"marks":35005,"text":35006},"3005d4859452",[],"f) exercising control over the physical access to personal data recorded on electronic media or contained on paper;",[],{"_key":35009,"_type":99,"children":35010,"markDefs":35015,"style":107},"01c97fbbdb19",[35011],{"_key":35012,"_type":103,"marks":35013,"text":35014},"737204e73588",[],"g) the adoption and adherence to a “clean workplace” policy;\nh) storage of personal data contained on paper in lockable wall cabinets;\ni) restricting the use by COSMOS THRACE employees of mobile electronic devices inside and outside the workplace;",[],{"_key":35017,"_type":99,"children":35018,"markDefs":35023,"style":107},"cb67428f98a6",[35019],{"_key":35020,"_type":103,"marks":35021,"text":35022},"9b1d86e89942",[],"j) adoption and observance of rules for creation and use of security passwords;\nk) regular backup of personal data and physical storage of media with copies outside the office;",[],{"_key":35025,"_type":99,"children":35026,"markDefs":35031,"style":107},"029115a05fed",[35027],{"_key":35028,"_type":103,"marks":35029,"text":35030},"6c27e73199c1",[],"l) the inclusion of obligations regarding the protection of personal data in contracts with suppliers, subcontractors, partners and third parties, as well as an obligation for them to take appropriate security measures when transferring data outside the EU.",[],{"_key":35033,"_type":99,"children":35034,"markDefs":35039,"style":107},"8b52a5472149",[35035],{"_key":35036,"_type":103,"marks":35037,"text":35038},"729c3d5003e5",[],"(3) All suppliers, subcontractors, partners, employees who work with or for COSMOS THRACE and who have or may have access to the personal data processed by COSMOS THRACE , shall be responsible for ensuring the security of the storage of personal data.\n(4) All suppliers, subcontractors, partners, employees who work with or for COSMOS THRACE and who have or may have access to the personal data processed by COSMOS THRACE , shall be obliged to store securely and not to disclose personal data to third parties, unless COSMOS THRACE has not granted the right of access to this data by concluding a confidentiality agreement for this purpose.",[],{"_key":35041,"_type":99,"children":35042,"markDefs":35047,"style":182},"fe66ceb99202",[35043],{"_key":35044,"_type":103,"marks":35045,"text":35046},"68cdb5de6caf",[],"XVI. CONFIDENTIALITY",[],{"_key":35049,"_type":99,"children":35050,"markDefs":35055,"style":107},"30766df9791f",[35051],{"_key":35052,"_type":103,"marks":35053,"text":35054},"876fbed53435",[],"(1) Personal data is subject to confidentiality. It is forbidden for employees to perform unauthorized collection, processing or use of personal data. Any processing performed by an unauthorized employee entrusted to him/her in the performance of his/her duties is unauthorized. The “need to know” principle applies: Employees can only access personal data if and to the extent necessary for their respective tasks. This requires careful division and separation of roles and responsibilities, as well as their implementation and maintenance within the scope of authorization concepts.",[],{"_key":35057,"_type":99,"children":35058,"markDefs":35063,"style":107},"c345e657a9b9",[35059],{"_key":35060,"_type":103,"marks":35061,"text":35062},"bb170090c762",[],"(2) Employees are not authorized to disclose personal information to unauthorized persons or in any other way or to use them for personal or economic purposes. Company managers must inform their employees of the obligation to protect the privacy of the data when they start work. This obligation shall remain in effect also after the employment of the employee concerned has ended.",[],{"_key":35065,"_type":99,"children":35066,"markDefs":35071,"style":107},"f1edd78766ac",[35067],{"_key":35068,"_type":103,"marks":35069,"text":35070},"9fde4d4c0185",[],"(3) Personal data must be protected against unauthorized access, unauthorized processing or disclosure, as well as accidental loss or destruction at any time. This applies irrespective of the processing of data electronically or in paper form.",[],{"_key":35073,"_type":99,"children":35074,"markDefs":35079,"style":107},"b27077311ba2",[35075],{"_key":35076,"_type":103,"marks":35077,"text":35078},"d1ab7ed1b4f3",[],"(4) Before implementing new processes or data processing, especially new information systems, all technical and organizational measures to protect personal data must be defined and implemented. These measures must be appropriate to the current technology standards, the risks arising from the processing and the need for data protection (defined by the classification process). The responsible department can consult with the corporate data protection officer. The technical and organizational measures for the protection of personal data are part of the management of the information safety of the Company and must be consistent with the technical changes and the organizational changes.",[],{"_key":35081,"_type":99,"children":35082,"markDefs":35087,"style":182},"0536e303b92c",[35083],{"_key":35084,"_type":103,"marks":35085,"text":35086},"1790f35a81bd",[],"XVII. VIOLATION OF THE SECURITY OF PERSONAL DATA",[],{"_key":35089,"_type":99,"children":35090,"markDefs":35095,"style":107},"e81bdca61276",[35091],{"_key":35092,"_type":103,"marks":35093,"text":35094},"38acdc4c9bde",[],"(1) The proper handling of personal data breaches is essential as the General Regulation provides for a very strict reporting requirement for data breaches. In the case of data security breaches, there are legal obligations to notify the supervising authority and the data subjects.",[],{"_key":35097,"_type":99,"children":35098,"markDefs":35103,"style":107},"22a11dcc205a",[35099],{"_key":35100,"_type":103,"marks":35101,"text":35102},"6e3e813cb1e8",[],"1. “Personal data breach” means a security breach that results in accidental or unlawful destruction, loss, alteration, unauthorized disclosure or access to personal data that is transmitted, stored or otherwise processed. The breach of data security is a breach of data security and data protection where it is probable or proven that personal data is known to unauthorized persons. Data security breaches often involve significant risks to the person concerned, such as damage to reputation, even credit card abuse or identity theft, as well as serious shortcomings for the company.",[],{"_key":35105,"_type":99,"children":35106,"markDefs":35111,"style":107},"45a2ef7c872f",[35107],{"_key":35108,"_type":103,"marks":35109,"text":35110},"5f4ed6e39958",[],"2. The General Regulation provides for a mandatory reporting requirement for data breaches. Art. 33 of the General Regulation (notification of the supervisory authority) and Art. 34 of that Regulation (for the notification of data subjects) determine when such an obligation is applicable.\n(2) In the case of a personal data breach, the controller shall without undue delay and, where feasible, not later than 72 hours after having become aware of it, notify the personal data breach to the supervisory authority competent in accordance with Art. 55, unless the personal data breach is unlikely to result in a risk to the rights and freedoms of natural persons. Where the notification to the supervisory authority is not made within 72 hours, it shall be accompanied by reasons for the delay.",[],{"_key":35113,"_type":99,"children":35114,"markDefs":35119,"style":107},"f2c47d1f6afe",[35115],{"_key":35116,"_type":103,"marks":35117,"text":35118},"e6c9c961db25",[],"(3) The processor shall notify the controller without undue delay after becoming aware of a personal data breach. The notification referred to in paragraph 1 shall at least:",[],{"_key":35121,"_type":99,"children":35122,"markDefs":35127,"style":107},"657779d934dc",[35123],{"_key":35124,"_type":103,"marks":35125,"text":35126},"6a5adb69497d",[],"1. Describe the nature of the personal data breach including where possible, the categories and approximate number of data subjects concerned, and the categories and approximate number of personal data records concerned.",[],{"_key":35129,"_type":99,"children":35130,"markDefs":35135,"style":107},"247c289000f6",[35131],{"_key":35132,"_type":103,"marks":35133,"text":35134},"d898469332a0",[],"2. Communicate the name and contact details of the data protection officer or other contact point where more information can be obtained.\n3. Describe the likely consequences of the personal data breach.\n4. Describe the measures taken or proposed to be taken by the controller to address the personal data breach, including, where appropriate, measures to mitigate its possible adverse effects.",[],{"_key":35137,"_type":99,"children":35138,"markDefs":35143,"style":107},"1c52bcffe0e5",[35139],{"_key":35140,"_type":103,"marks":35141,"text":35142},"29a39d140559",[],"Where, and in so far as, it is not possible to provide the information at the same time, the information may be provided in phases without undue further delay.",[],{"_key":35145,"_type":99,"children":35146,"markDefs":35151,"style":107},"a13240e46146",[35147],{"_key":35148,"_type":103,"marks":35149,"text":35150},"ed1d0861a46e",[],"(4) The controller shall document any personal data breaches, comprising the facts relating to the personal data breach, its effects and the remedial action taken. That documentation shall enable the supervisory authority to verify compliance with Art. 33 of the General Regulation.",[],{"_key":35153,"_type":99,"children":35154,"markDefs":35159,"style":107},"30fef283c5eb",[35155],{"_key":35156,"_type":103,"marks":35157,"text":35158},"9dd854f14194",[],"(5) When the personal data breach is likely to result in a high risk to the rights and freedoms of natural persons, the controller shall communicate the personal data breach to the data subject without undue delay.",[],{"_key":35161,"_type":99,"children":35162,"markDefs":35167,"style":107},"671cadc12740",[35163],{"_key":35164,"_type":103,"marks":35165,"text":35166},"89ca41220829",[],"(6) The communication to the data subject presented above shall describe in simple manner the nature of breach in the security of personal data, covering at least:\n1. Communicates the name and contact details of the data protection officer or other contact point where more information can be obtained.\n2. Describe the likely consequences of the violation of personal data.\n3. Describes the measures taken or suggested by the controller to handle the personal data breach, including, where appropriate, mitigation measures for possible adverse effects.",[],{"_key":35169,"_type":99,"children":35170,"markDefs":35175,"style":107},"f60b163042a4",[35171],{"_key":35172,"_type":103,"marks":35173,"text":35174},"135edc7e0745",[],"(7) The above message to the data subject is not required if any of the following conditions are met:",[],{"_key":35177,"_type":99,"children":35178,"markDefs":35183,"style":107},"5e1215d86cf1",[35179],{"_key":35180,"_type":103,"marks":35181,"text":35182},"c803733ec6a9",[],"1. The controller has implemented appropriate technical and organizational protection measures, and those measures were applied to the personal data affected by the personal data breach, in particular those that render the personal data unintelligible to any person who is not authorized to access it, such as encryption.\n2. The controller has taken subsequent measures which ensure that the high risk to the rights and freedoms of data subjects referred to in Art. 34(1) of the General Regulation is no longer likely to materialize.",[],{"_key":35185,"_type":99,"children":35186,"markDefs":35191,"style":107},"1e64e39c5ea8",[35187],{"_key":35188,"_type":103,"marks":35189,"text":35190},"6b92febefc5b",[],"3. It would involve disproportionate effort. In such a case, there shall instead be a public communication or similar measure whereby the data subjects are informed in an equally effective manner.",[],{"_key":35193,"_type":99,"children":35194,"markDefs":35199,"style":107},"6887d6687d82",[35195],{"_key":35196,"_type":103,"marks":35197,"text":35198},"84ff590e41ae",[],"(8) If the controller has not already communicated the personal data breach to the data subject, the supervisory authority, having considered the likelihood of the personal data breach resulting in a high risk, may require it to do so or may decide that at least one of the conditions listed above is met (ref. Art. 34(3) of the General Regulation).",[],{"_key":35201,"_type":99,"children":35202,"markDefs":35207,"style":182},"d52fdf4313b0",[35203],{"_key":35204,"_type":103,"marks":35205,"text":35206},"2fd576003dbd",[3055],"XVIII. WEBSITE TRACKING, COOKIES AND ONLINE ADVERTISING",[],{"_key":35209,"_type":99,"children":35210,"markDefs":35215,"style":107},"f99e4c3f2ad9",[35211],{"_key":35212,"_type":103,"marks":35213,"text":35214},"d41e80a9575a",[],"(1) When you visit or log in to our website, cookies and similar technologies may be used by our online data partners or vendors to associate these activities with other personal information they or others have about you, including by association with your email address. We (or service providers on our behalf) may then send communications and marketing to these email addresses.",[],{"_key":35217,"_type":99,"children":35218,"markDefs":35227,"style":107},"02fad4910591",[35219,35223],{"_key":35220,"_type":103,"marks":35221,"text":35222},"0e8805ef2ede",[],"(2) ",{"_key":35224,"_type":103,"marks":35225,"text":35226},"0cc00f789657",[3055],"Third-Party Data Processing Partners",[],{"_key":35229,"_type":99,"children":35230,"markDefs":35235,"style":107},"cedd529ef4a3",[35231],{"_key":35232,"_type":103,"marks":35233,"text":35234},"54698b5c627d",[],"COSMOS THRACE uses RB2B (operated by Retention.com) as a website visitor identification service. 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