As one of Germany's largest energy providers, EnBW Vertrieb (Sales Business Unit) is modernizing its enterprise data platform to better serve customers, accelerate analytics, and prepare for AI. As the organization migrated from Azure Synapse to Databricks, it needed a governance foundation that could scale with its growing data mesh. By adopting Unity Catalog, EnBW centralized governance across business domains, improved discoverability and trust in enterprise data, and simplified how more than 150 data practitioners securely access and manage data across the organization.
Building the foundation for a data mesh
EnBW's data platform supports a wide range of customer-facing analytics, from call center forecasting and customer service optimization to pricing decisions and customer retention initiatives. As adoption grew, the team began transitioning away from Azure Synapse toward a unified Lakehouse architecture on Databricks.
At the same time, the organization was evolving its operating model. Rather than relying on a centralized analytics team, EnBW was moving toward a data mesh approach in which individual business domains own and manage their data products. While this created greater flexibility, it also introduced new governance challenges. Data existed across multiple workspaces, ownership was fragmented, access management relied on manual processes, and users often struggled to identify which datasets were trusted or who was responsible for maintaining them.
"Before, users had to work backward through pipelines to understand where a KPI came from or who owned the data quality," said Martin Kalusa, Solutions Architect at Databricks and former Data Platform Architect at EnBW. "Those responsibilities weren't always clear."
The team also encountered duplicate business metrics across departments, with different teams independently recreating KPIs that shared the same name but produced different results. Without consistent governance and visibility, establishing a single source of truth became increasingly difficult as the platform expanded.
Centralizing governance with Unity Catalog
To support both its platform modernization and its new organizational model, EnBW implemented Unity Catalog as the centralized governance layer for its Databricks lakehouse.
The platform team organized data into domain-specific catalogs that mirror the company's business structure, making it easier for users to discover trusted data products while allowing each domain to own its data independently. Built-in lineage helps users understand how datasets are created, certification identifies trusted Gold-layer data products, and centralized auditing provides greater visibility into who is accessing sensitive customer information.
For EnBW, governance also became significantly easier to manage. Automated access workflows integrated with Microsoft Entra ID replaced manual permission requests, improving both auditability and operational efficiency while helping satisfy GDPR requirements for customer data.
"Unity Catalog made it much easier to implement our organizational structure," said Schmidt. "Each domain can own its own catalog while we maintain centralized governance across the platform."
As part of its modernization effort, EnBW also uses Lakehouse Federation to connect existing data sources in Azure Synapse, Snowflake, and Google BigQuery. This allows business teams to continue accessing legacy data while progressively migrating workloads to Databricks without disrupting day-to-day operations.
Accelerating trusted analytics and future AI initiatives
Today, EnBW processes approximately five terabytes of data every day on Databricks while supporting more than 150 data practitioners across the organization.
The migration has already delivered measurable operational improvements. One of the company's primary ingestion pipelines was reduced from approximately five hours to just one and a half hours, allowing downstream analytics and customer-facing use cases to operate on fresher data.
Perhaps more importantly, EnBW has established the governance foundation needed to continue scaling. Trusted data products, centralized lineage, standardized ownership, and automated access management allow new business domains to onboard more quickly while maintaining consistent governance across the enterprise.
Looking ahead, EnBW plans to expand its use of Databricks with Business Semantics, AI/BI Dashboards, customer data platform integrations, and AI governance capabilities. Because governance has already been established through Unity Catalog, the organization is well-positioned to adopt these new AI capabilities on a trusted, governed foundation.
"We're moving toward a future where governance is built directly into the EnBW platform," Kalusa said. "That gives their teams confidence to innovate faster while ensuring everyone is working from trusted data."
