Power BI dashboards using Direct Lake
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yesterday
Hi Everyone, We are experimenting with using Direct Lake for our Power BI dashboards and I wanted to check in with this group to see if people have tried or are currently using this to connect PBI to Databricks tables. If so what is your experience with performance and in particular data governance?
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yesterday
- Direct Query on Databricks SQL Warehouses
- Import mode for scheduled batch extracts
- OpenSharing / Delta Sharing connector for cross-platform data exchange.
- 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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yesterday
Your Power Bi report needs to be in Fabric capacity workspace in order for you leverage Direct Lake mode functionality.
So you can try the path of Databricks mirroring :
Fabric mirrors Unity catalog metadata and creates OneLake shortcuts to the Delta files in ADLS; no data movement, and no Databricks cluster needs to be running because Fabric reads storage directly using credential vending from Unity catalog. You get an auto-generated read-only SQL analytics endpoint and can build a Direct Lake model over it :
Based on what I remember Unity catalog permissions do not carry across. Mirroring replicates metadata and file pointers, not ACLs, so Fabric becomes a second, independently-administered security perimeter. Column masks, row filters and dynamic views in UC all have to be re-authored.