Databricks Consulting & Implementation

Databricks unifies data from all sources into one lakehouse, eliminating silos and enabling consistent access for analytics and AI across your organization.

Databricks delivers 10-100x faster query performance compared to legacy systems like Teradata and Oracle, enabling real-time insights instead of overnight batch processing.

Unity Catalog provides centralized governance with clear data lineage, automated access controls, and compliance frameworks that make regulatory audits straightforward.

Databricks optimizes compute and storage separation, auto-scaling clusters, and intelligent caching to reduce infrastructure spend by 30-60% compared to traditional cloud warehouses.

Databricks provides a unified, governed foundation where data scientists can build, train, and deploy ML models at scale using MLflow, AutoML, and enterprise-grade AI frameworks.

Databricks automates data processing with built-in quality controls and real-time pipelines, ensuring all dashboards and reports use a single source of truth with validated, consistent data.

Implementation costs vary based on your data volume, complexity, and migration scope.

We start every project with a transparent assessment that defines costs upfront, breaking them down by phase so your CFO sees exactly what you're investing in at each stage.

Typical enterprise implementations range from €50K for focused use cases to €300K+ for full-scale migrations with AI enablement.

Most Databricks migrations take 3-6 months from discovery to production, depending on data volume and legacy system complexity.

We use a phased approach with weekly progress updates, starting with a 4-6 week pilot to validate architecture before full rollout.

This reduces risk and lets your stakeholders see working results early rather than waiting months for a "big bang" launch.

Enterprises typically achieve three major benefits: 10-100x faster query performance compared to legacy warehouses, 30-60% reduction in infrastructure costs through optimized compute and storage, and unified data governance through Unity Catalog that makes compliance straightforward.

The lakehouse architecture also eliminates data silos, enabling AI and machine learning at scale without building separate infrastructure.

Databricks provides enterprise-grade security through Unity Catalog, which centralizes data governance with role-based access controls, automated data lineage tracking, and audit logging.

We implement governance frameworks where your security team defines policies, data stewards manage access, and business users follow clear rules they actually understand.

This makes compliance audits straightforward and gives executives full visibility into who accesses what data.

Databricks is ideal when you need unified data and AI capabilities in one platform, especially if you're dealing with large-scale data processing, real-time analytics, or machine learning workflows.

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.

If you're only running simple BI dashboards with no AI plans, Snowflake or traditional BI tools might be more cost-effective.