Authored by Microsoft Fabric Blog, with contributions from Peri Rocha, Ancy Philip, Jovan Popovic, and Twinkle Cyril, this article unveils the latest enhancements to Fabric Data Warehouse supporting advanced analytics and modern data warehousing.

Microsoft Fabric Data Warehouse: Enterprise-Ready Features Announced at Ignite

Authors: Microsoft Fabric Blog, Peri Rocha, Ancy Philip, Jovan Popovic, Twinkle Cyril

Microsoft Fabric Data Warehouse has evolved rapidly since general availability, introducing multiple performance and usability enhancements designed for enterprise analytics and modern data management.

Key Enhancements

1. Data Clustering (Preview)

2. IDENTITY Columns (Preview)

  • Automatic surrogate key generation during ingestion.
  • Eliminates manual key assignment and risk of duplication.
  • Ensures uniqueness, even with parallel data jobs.
  • Documentation – IDENTITY Columns

3. VARCHAR(MAX) and VARBINARY(MAX) Support

  • Support for very large string and binary columns (up to 16MB per cell).
  • Enables ingestion and analysis of logs, descriptive text, JSON, spatial data, and more.
  • SQL endpoint now reads large objects from source systems without former 8KB truncation.
  • Auto upgrade for existing tables as schemas change, preventing corruption (notably for Cosmos DB JSON artifacts).

4. Warehouse Snapshots (GA)

  • Point-in-time, read-only views for consistency in reporting and ETL.
  • Solves issues with “half-loaded” data disrupting reporting and dashboards.
  • Enables reliable time-travel queries.
  • More on Warehouse Snapshots

Platform Overview

Fabric Warehouse integrates ETL, SQL, BI, AI, and operational apps into a unified analytics platform. New capabilities empower organizations to scale and innovate with performance, scalability, and cost-effectiveness.

Getting Started & Resources

Summary

These enhancements position Microsoft Fabric Data Warehouse as a comprehensive solution for enterprise data warehousing, analytics engineering, and large-scale BI, addressing challenges like performance, consistency, and complex schema management.

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