About This Architecture

Azure Databricks Enterprise Lakehouse Architecture implements a medallion storage pattern ingesting data from SAP ERP, RDBMS, APIs, and files through batch and CDC pipelines into Bronze raw layer. Data flows through Silver cleaned and Gold business-ready layers via Databricks Jobs and Pipelines orchestration, with Unity Catalog providing governance across all tiers. Processing layers enable data transformation, feature engineering, and ML model development via MLflow, feeding predictions to Power BI, Databricks AI/BI, Genie, and enterprise systems through Delta Sharing. This architecture demonstrates enterprise-grade data governance, scalable ETL, and integrated AI/ML capabilities essential for organizations requiring unified analytics and ML operations. Fork this diagram on Diagrams.so to customize data sources, add custom transformations, or adapt the governance model for your organization's compliance requirements.

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How do I design a scalable enterprise lakehouse on Azure Databricks with proper data governance and ML integration?

This diagram shows a complete Azure Databricks lakehouse using medallion storage (Bronze/Silver/Gold layers), Unity Catalog for governance, Databricks Jobs and Pipelines for orchestration, and MLflow for model management. Data ingests from SAP ERP, RDBMS, APIs, and files through batch and CDC, transforms through processing layers, and serves predictions to Power BI, Databricks AI/BI, and enterpris