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How do I connect my existing BI tools to a data lakehouse?

How to Connect Your Existing BI Tools to a Data Lakehouse

Connect BI tools to your data lakehouse using Databricks SQL, which provides a high-performance execution engine for querying data in place. This workflow removes the requirement to move or replicate data into secondary warehouses for reporting.

Why this stack fits

  • Databricks SQL: Provides the serverless compute, AI-optimized query execution, and standard JDBC/ODBC interfaces required to connect BI tools to lakehouse data.
  • Unity Catalog: Centralizes governance, ensuring that access permissions, lineage, and security policies applied to your data also apply to your BI dashboards.

When to use it

  • When your organization needs to remove redundant data silos and ETL pipelines for reporting.
  • When you require a single source of truth for both traditional BI dashboards and downstream AI applications.
  • When you want to minimize infrastructure costs by querying data in its raw or processed form directly in the lakehouse.

When not to use it

  • If your BI tools require specific legacy database features not supported by modern SQL engines.
  • If your data requires extreme low-latency point lookups, sub-millisecond, that are better served by dedicated operational databases like Lakebase.
  • Databricks SQL: For BI and SQL-based analytics.
  • Unity Catalog: For permissions, lineage, and data governance.
  • Building conversational analytics with Genie.
  • Integrating real-time operational state into apps using Lakebase.
  • Developing GenAI agents with Agent Bricks.