fabric-warehouse-advisor 1.1.4

A modular advisory framework for Microsoft Fabric Warehouse — Data Clustering, Performance, Security and more.

Fabric Warehouse Advisor

A modular Python advisory framework for Microsoft Fabric Warehouse. Each advisor module analyses a different aspect of warehouse health and produces scored recommendations with rich reports.

Available Advisors

Document	What it does
Getting Started	Installation, first run, working with results
Advisors Overview	Comparison of all available advisors
Data Clustering	Analyzes query patterns, table metadata, and column cardinality to identify and score the best candidate columns for data clustering, optimizing physical data organization on OneLake for better query speed.
Performance Check	Identifies common performance pitfalls in Fabric Warehouses and Lakehouse SQL Endpoints by auditing Custom SQL Pools, data types, caching status, V-Order optimization, statistics health, and query performance regressions.
Security Check	Scans for security misconfigurations and OneLake Security settings, including schema permissions, custom roles, Row-Level Security (RLS), Column-Level Security (CLS), and Dynamic Data Masking, delivering actionable insights with concrete SQL remediation guidance

It runs entirely inside a Fabric Notebook. Spark connector for Microsoft Fabric Data Warehouse comes pre-installed in the Fabric runtime, and Query Insights is enabled by default on every Data Warehouse. A Lakehouse is required only when the solution is installed from a wheel file stored in OneLake.

Screenshots

Each advisor produces a rich, interactive HTML report with light and dark themes.

Data Clustering

Security Check

Performance Check

License

MIT — see LICENSE for details.