Edit, Retarget, and Redeploy: A Practical TMDL Folder Workflow for Fabric Semantic Models

There’s a moment in every Fabric semantic model lifecycle where the “click it in the UI” approach stops scaling.

It usually happens when you need to rename dozens (or hundreds) of fields to match a business glossary, or when Dev is stable and you’re ready to point the same model at a new Lakehouse for Test/Prod. That’s when the model stops being a diagram and starts being an artifact—something you want to treat like code.

This guide reflows the whole workflow end-to-end, using the Fabric service Edit in Desktop experience to open the model, exporting it to a PBIP project stored as a TMDL folder, editing that folder externally (no scripting inside Power BI Desktop), and then getting those changes back into the service—including the key capability you asked for:

  • retargeting the entire model to a different Lakehouse/Warehouse, and
  • retargeting a single table to a different physical table (even in a new Lakehouse).

We’ll do it with the mindset of Power BI + Microsoft Fabric development: repeatable changes, visible diffs, and fewer “hand edits” you regret later.

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The Microsoft Fabric Delta Change Data Feed (CDF)

In Microsoft Fabric you’re sitting on top of Delta Lake tables in OneLake. If you flip on Delta Change Data Feed (CDF) for those tables, Delta will record row‑level inserts, deletes, and updates (including pre‑/post‑images for updates) and let you read just the changes between versions. That makes incremental processing for SCDs (Type 1/2) and Data Vault satellites dramatically simpler and cheaper because you aren’t rescanning entire tables—just consuming the “diff.” Fabric’s Lakehouse fully supports this because it’s natively Delta; Mirrored databases land in OneLake as Delta too, but (as of September 2025) Microsoft hasn’t documented a supported way to enable Delta CDF on the mirrored tables themselves; you can still analyze mirrored data with Spark via Lakehouse shortcuts, or source CDC upstream (Real‑Time hub) and write to your own Delta tables with CDF enabled.

This feature is already underutilized, but once Mirrored Databases support the CDF, it’s going to be a must have in every data engineer’s toolkit.

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