Power BI

Connect Power BI Desktop to a Databricks SQL warehouse, build a model against a gold table, publish a thin report. About thirty minutes.

Three ways Power BI can talk to Databricks, one right default, and the traps that trip teams up on AWS deployments and DirectQuery.

Four modes, increasingly overlapping, with a clear decision tree. When Import stops being the right default.

Datasets are called semantic models now and the term matters. The canonical pattern for one model per domain, many thin reports, and how Databricks metric views close the double-definition problem.

DirectQuery performance is a joint responsibility between your Power BI model and your warehouse. The full tuning checklist.

Stop using the UI scheduler. The Enhanced Refresh REST API, incremental policies, and Airflow integration that prevent stale dashboards after a failed upstream build.

Stop committing .pbix. The folder format and TMDL files that finally make Power BI diff-friendly, review-friendly, and merge-friendly.

Deploy PBIP artifacts through dev, staging, and prod workspaces with a service principal, BPA gates, and post-deploy refresh tests.

Three production tools, distinct roles, and the commands you actually use day to day.

The Causeway rules for a Power BI semantic model: shape, connectivity, DAX, storage mode, versioning. Enforced in PR review via BPA.

What a shared semantic model must satisfy before its first prod deploy, and keep satisfying after. Enforced at the Certified-endorsement gate.

The handful of DAX rules that cover 80% of production performance and correctness issues, plus the patterns to avoid.