Is it better to use Power BI Dataflows or a dedicated SQL Data Warehouse for enterprise ETL?

All answers to this question.

Dataflows are fantastic for "Self-Service BI" because they allow analysts who know Power Query to build reusable entities without needing to write T-SQL. However, for a mid-sized company looking to scale, a dedicated SQL Warehouse offers better performance for complex transformations and better integration with other tools like Python or R. Dataflows live within the Power BI Service, which can make debugging large-scale transformations a bit opaque. If your data volume is under 1TB and your team is primarily Power BI focused, Dataflows will be faster to deploy and cheaper initially.

   Answered 2025-10-15 by Deborah Lewis

If we go the Dataflows route, how do we handle version control? Since it's all in the Power BI Service UI, isn't it hard to track changes compared to SQL scripts in a Git repo?

   Answered 2025-10-18 by Christopher Evans

• You hit the nail on the head, Christopher. To manage that, we use the "Deployment Pipelines" feature in Power BI Premium, which allows us to move Dataflows from Dev to Test to Production. While it's not as granular as a Git commit for a SQL script, it provides a structured release process. We also export the .json definition of the Dataflow and store it in our repository manually as a backup, which gives us a history of logic changes over time.

     Commented 2025-10-22 by David Miller

Why not use both? You can use a SQL Warehouse for the heavy lifting and then use Dataflows as a semantic layer for specific departments to add their own light transformations.

   Answered 2025-10-25 by Jennifer Foster

• This hybrid approach is actually what we do at my firm. It gives the IT team control over the "Source of Truth" while giving business units the flexibility they need.

     Commented 2025-10-28 by David Miller