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Microsoft Fabric Updates Blog

  1. 更新
  2. Lakehouse

Best-in-class connectivity and data movement with Data Factory in Fabric

In the fast-evolving data integration landscape, Data Factory continues to enhance the existing connectors to provide high-throughput data ingestion experience with no-code, low-code experience. With a focus on improving connector efficiency and expanding capabilities, recent updates bring significant advancements to a number of connectors. These improvements focus on: Latest innovations 1. Lakehouse connector now supports … Continue reading “Best-in-class connectivity and data movement with Data Factory in Fabric”

Playbook for metadata driven Lakehouse implementation in Microsoft Fabric

  • Headshot of article author 4月 2, 2025 作者： RK Iyer 146,570 點閱數

Co-Author – Gyani Sinha, Abhishek Narain Overview A well-architected lakehouse enables organizations to efficiently manage and process data for analytics, machine learning, and reporting. To achieve governance, scalability, operational excellence, and optimal performance, adopting a structured, metadata-driven approach is crucial for lakehouse implementation. Building on our previous blog, Demystifying Data Ingestion in Fabric, this post … Continue reading “Playbook for metadata driven Lakehouse implementation in Microsoft Fabric”

High Concurrency mode for notebooks in pipelines (Generally Available)

High Concurrency mode for notebooks in pipelines is now generally available (GA)! This powerful feature enhances enterprise data ingestion and transformation by optimizing session sharing within one of the most widely used orchestration mechanisms. With this release, we’re also introducing Comprehensive Monitoring for High-Concurrency Spark Applications, bringing deeper visibility and control to your workloads. Key … Continue reading “High Concurrency mode for notebooks in pipelines (Generally Available)”

Supercharge your workloads: write-optimized default Spark configurations in Microsoft Fabric

Introducing predefined Spark resource profiles in Microsoft Fabric—making it easier than ever for data engineers to optimize their compute configurations based on workload needs. Whether you’re handling read-heavy, write-heavy, or mixed workloads, Fabric now provides a property bag-based approach that streamlines Spark tuning with just a simple setting. With these new configurations, users can effortlessly … Continue reading “Supercharge your workloads: write-optimized default Spark configurations in Microsoft Fabric”

Easily load Fabric OneLake data into Excel — OneLake catalog and Get Data are integrated into Excel for Windows (Preview)

  • Headshot of article author 3月 31, 2025 作者： Penny Zhou 43,497 點閱數

We are excited to announce that the Get Data experience, along with the OneLake catalog, is now integrated into Excel for Windows (Preview). Like OneDrive, OneLake is a single, unified, logical data lake for your whole organization analytics data. This makes it crucial to have a streamlined method for loading OneLake data into Excel, enabling … Continue reading “Easily load Fabric OneLake data into Excel — OneLake catalog and Get Data are integrated into Excel for Windows (Preview)”