Overview Microsoft Fabric is officially sunsetting Default Semantic Models. This change is part of our ongoing efforts to simplify and improve the manageability, deployment, and governance of Fabric items such as warehouse, lakehouse, SQL database, and mirrored databases. Why the Change? Default Semantic Models were initially designed to provide a lightweight, out-of-the-box experience—automatically generating models …
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Fabric offers a wide variety of data-science capabilities, from automated machine learning with FLAML to batch inferencing with the SynapseML PREDICT function. We’re pleased to announce that ML models can now serve real-time predictions from secure, scalable, and easy-to-use online endpoints. In addition to generating batch predictions in Spark, you can use endpoints to bring …
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We’re thrilled to share a series of exciting updates and upcoming enhancements to the SQL analytics endpoint in Microsoft Fabric. These improvements are designed to make your experience more powerful and reliable. From Preview to GA – Metadata sync REST API Last month, we introduced the SQL analytics endpoint metadata sync REST API in preview, …
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Microsoft Fabric offers native Git integration and deployment pipelines to facilitate version control, collaboration, and automated releases for workspace items like user data functions. This guide explains how to set up and manage Git integration for user data functions within a Fabric workspace.
• Workspace preparation and Git linking: Users start by selecting or creating a Fabric workspace containing user data functions, then enable Git integration via workspace settings by connecting to a Git provider and repository branch, optionally specifying a folder for organization.
• Branching strategy configuration: Teams are advised to adopt branching strategies such as main/develop, feature, and release branches, along with pull request and code review policies to maintain code quality and collaboration.
• Managing user data functions in Git: Each data function is stored in a function_app.py file; users clone the repository locally, edit or add functions, and update the definition.json file to reflect new functions and required libraries like numpy.
• Committing, syncing, and publishing changes: After committing changes in VS Code, users sync with the Fabric portal, update the function via source control, and publish to deploy the new or updated functions, making them available for invocation.
Shortcut‑based AI transformations in Microsoft Fabric convert raw text files into governed Delta Lake tables within minutes, removing the need for complex data‑integration pipelines and significantly reducing time to insight. Why adopt AI transformations? Supported AI transforms Transform Purpose Summarization Generates concise summaries from long-form text. Translation Translates text between supported languages. Sentiment analysis Labels text …
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