Data Architecture & Modernization Services

We unify data sources into a structured architecture with shared models and governed pipelines.

This ensures that every dashboard and report is based on consistent, reliable data.

Your teams track progress through weekly updates showing exactly which systems are integrated and validated.

We establish automated data quality checks, validation rules, and monitoring that catch issues before they reach your reports.

Your data stewards define quality standards, and your business teams see real-time data quality scores they can trust.

We implement clear data ownership, role-based access controls, and audit logging that satisfy regulatory requirements.

Your security team sets policies, your compliance officers track them, and your business users follow rules they actually understand.

We replace manual steps with automated ingestion, transformation, and validation pipelines.

This eliminates errors, speeds up workflows, and frees your teams from repetitive tasks.

You see exactly what's automated and what manual processes remain.

We modernize your data platform with scalable cloud infrastructure and optimized pipelines, improving performance by 10-100x.

Your CFO tracks cost savings, your CTO reviews the technical architecture, and your analysts get faster query response times.

We design centralized data models and unified storage layers that serve as a single reliable foundation for analytics, BI, and AI.

Every stakeholder from executives to analysts works from the same validated datasets with clear documentation of what each field means.

Data modernization projects typically range from €75K for focused initiatives (single data source integration, governance framework) to €400K+ for enterprise-wide transformations (multiple legacy systems, full pipeline architecture, BI implementation).

We start every engagement with a transparent cost breakdown showing infrastructure, migration, training, and support costs separately.

Your CFO receives ROI projections based on measurable outcomes: reduced manual processing time, infrastructure cost savings (typically 30-40% moving to cloud), and compliance risk mitigation.

Enterprise data projects typically span 4-8 months from discovery to production, depending on data volume, system complexity, and organizational readiness.

We use a phased approach: 4-6 week pilot validates architecture and builds stakeholder confidence, then incremental rollout with weekly progress dashboards showing exactly what's migrated, tested, and production-ready.

This prevents "big bang" failures and lets your teams adapt gradually rather than facing a single high-risk cutover weekend.

We use multi-layer validation at every migration phase: pre-migration data profiling, row count verification, checksum validation, and reconciliation reports comparing source and target systems.

Your CTO reviews our rollback procedures before any cutover, and we maintain parallel systems during transition so legacy data remains accessible if issues arise.

Monthly data quality reports show completeness, accuracy, and consistency metrics your compliance team can audit.

We design governance frameworks from day one rather than adding compliance as an afterthought.

This includes data classification, role-based access controls, audit logging, and automated data lineage tracking that satisfy regulatory requirements.

Your security team defines policies, your compliance officers track them through monthly governance reviews, and your business users follow documented procedures they actually understand, preventing the "security vs usability" conflict that derails many governance initiatives.

Most enterprises adopt a hybrid model: consultants handle specialized expertise (migration methodology, architecture design, compliance frameworks) while your internal teams manage ongoing operations and retain institutional knowledge.

We explicitly transfer knowledge through role-specific training, your data engineers learn platform management, your analysts learn self-service tools, your executives learn KPI interpretation.

This prevents consultant dependency while letting you access expertise that would take years to build internally.

We offer tiered support options from basic monitoring (monthly health checks, performance reports) to full managed services (24/7 support, continuous optimization, governance reviews).

During the transition period, we provide 3-6 months of hands-on support as your teams gain confidence managing the platform independently.

Monthly reports track system performance, data quality metrics, and usage statistics in business terms your executives understand, not just technical metrics.