📘 Notebook Description
The notebook is designed to extract, enrich, and visualize semantic model metadata and measure-level dependencies within Microsoft Fabric. It connects to a specified semantic model, retrieves tables, columns, measures, and relationships, and enhances measures with AI-generated business descriptions. The notebook then derives measure-to-measure dependencies from DAX expressions, builds a Directed Acyclic Graph (DAG), and presents both tabular lineage outputs and graph-based visualizations. This enables a deep understanding of how calculations are structured and interrelated within the semantic model.
🌟 Benefits
Measure Lineage Transparency: Provides clear visibility into how measures are built on top of one another, improving model understanding and governance.
AI-Powered Documentation: Automatically generates business-friendly descriptions for DAX measures, reducing manual documentation effort.
Impact Analysis: Identifies upstream and downstream dependencies between measures, helping assess the impact of logic changes
GitHub URL : https://github.com/NandanHegde15/MSFTFabric-Notebook/blob/main/SemanticModel/Metadata%20Extraction/2...
https%3A%2F%2Fgithub.com%2FNandanHegde15%2FMSFTFabric-Notebook%2Fblob%2Fmain%2FSemanticModel%2FMetadata%2520Extraction%2F2026_SemanticLink_NandanHegde_MetadataExtractor.ipynb
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Nandan Hegde (MSFT Data MVP)
LinkedIn Profile : www.linkedin.com/in/nandan-hegde-4a195a66
GitHUB Profile : https://github.com/NandanHegde15
Twitter Profile : @nandan_hegde15
MSFT MVP Profile : https://mvp.microsoft.com/en-US/MVP/profile/8977819f-95fb-ed11-8f6d-000d3a560942
Topmate : https://topmate.io/nandan_hegde
Blog :https://datasharkx.wordpress.com
