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Microsoft Fabric Updates Blog

  1. Updates
  2. Michaela Isaacs

Announcing Staging for Mirroring for Google BigQuery (Preview)

Introducing staging support for Mirroring for Google BigQuery (Preview), a major enhancement that dramatically improves the speed and efficiency of initial data replication from Google BigQuery into Microsoft Fabric. Why Staging Matters Previously, initial replication of large datasets from BigQuery into Fabric could be time-consuming. With staging enabled, organizations are now seeing performance improvements of … Continue reading “Announcing Staging for Mirroring for Google BigQuery (Preview)”

Mirroring for Google BigQuery in Microsoft Fabric (Preview)

This new capability extends Microsoft Fabric’s zero-ETL data movement strategy, enabling customers to replicate data from BigQuery into OneLake—securely, efficiently, and in near real-time. What is Mirroring? Mirroring in Microsoft Fabric allows customers to replicate their operational and warehouse data sources directly into OneLake without complex ETL pipelines. This ensures data stays fresh and is … Continue reading “Mirroring for Google BigQuery in Microsoft Fabric (Preview)”

Decoupling Semantic Model for Mirroring Customers

Overview Semantic models are evolving to work more seamlessly with Mirrored artifacts—giving you greater flexibility, control, and transparency when working with mirrored data. Why are we decoupling semantic models from Mirroring Artifacts? Historically, Mirrored artifacts were created with an automatically ‘coupled’ semantic model. While convenient out-of-the-box, this approach limited how you could shape, interpret, and … Continue reading “Decoupling Semantic Model for Mirroring Customers”