microsoft/semantic-link-labs

Early access to new features for Microsoft Fabric's Semantic Link.

What it solves

Semantic Link Labs is a Python library that simplifies the management and optimization of Microsoft Fabric and Power BI assets. It automates technical, repetitive tasks—such as migrating semantic models, analyzing report performance, and managing lakehouse tables—allowing users to focus on higher-level data engineering and analysis activities.

How it works

It acts as an extension to the Semantic Link library, providing a set of wrapper functions and specialized tools for use within Microsoft Fabric notebooks. It integrates with Power BI, Fabric, Azure, and Microsoft Graph APIs to programmatically control semantic models, reports, capacities, and lakehouses.

Who it’s for

Data engineers, data scientists, and Power BI developers working within the Microsoft Fabric ecosystem who need to automate the administration and optimization of their data models and reports.

Highlights

  • Semantic Model Management: Automates migration to Direct Lake, performs best practice analysis, manages backups/restores, and auto-generates measure descriptions.
  • Report Optimization: Identifies broken visuals, analyzes object usage frequency, and migrates report-level measures to semantic models.
  • Infrastructure Control: Programmatically creates, updates, suspends, or resumes Fabric capacities.
  • Lakehouse Maintenance: Provides tools to optimize and vacuum lakehouse tables and recover soft-deleted objects.
  • API Integration: Includes wrapper functions for Power BI, Fabric, Azure, and Microsoft Graph APIs.

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