balajij8
Esteemed Contributor II

yesterday

@dbernstein_tp 

 
Direct Lake is a Fabric feature designed to read Delta/Parquet files directly from One Lake storage.  For standard Power BI to Databricks cases (Power BI reports directly from Databricks tables), you can use below
  • Direct Query on Databricks SQL Warehouses
  • Import mode for scheduled batch extracts
  • OpenSharing / Delta Sharing connector for cross-platform data exchange.
If data governance is the primary requirement, Direct Query is the recommended path. Because Direct Query sends native SQL queries back to the warehouse at runtime, all Unity Catalog security primitives including table permissions, row-level filters and column masks are strictly evaluated and enforced per user session. You can set large fact tables in Direct Query while configuring dimension tables to Dual mode if feasible that allows Power BI to optimize cross-table join execution plans while preserving access controls.

To hit sub 5 second interactive dashboard SLAs with Direct Query while maintaining live Unity Catalog governance, consider below
  • Composite Models and Aggregations - Implement user-defined or automatic aggregation tables to serve high-level summarized metrics instantly while allowing drill-through to detail rows via Direct Query.
  • Transformations at Source - Push complex business logic and transformations upstream into Databricks SQL views or materialized tables rather than relying on heavy DAX calculations.
  • Warehouse Sizing and Concurrency - Configure query parallelization and scale out cluster endpoints on your SQL Warehouse to prevent visual concurrency bottlenecks during peak dashboard usage.

More details here

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