Validate your Fabric semantic model against your Lakehouse automatically.
This notebook pairs DAX queries with Spark SQL queries and compares the results at the DataFrame level. It handles DAX column name normalization, floating-point tolerance for numeric comparisons, and detailed mismatch reporting. Define test cases as DAX/SQL query pairs, run the harness, and get a pass/fail summary showing where your semantic model and Lakehouse disagree. Useful as a post-refresh validation step or for detecting schema drift in models that sit on Gold-layer lakehouse tables.
Author: Jens Vestergaard · Head of Product, CatMan @ Redslim
Built on: Semantic Link Labs by Michael Kovalsky
https%3A%2F%2Fgithub.com%2Fvestergaardj%2FSemantic-Link-TestHarness%2Fblob%2Fmain%2F2026_SemanticLink_vestergaardj_SemanticTestVsLakehouse.ipynb
