Fabric changes
Microsoft's edit ·
Microsoft's commit message in MicrosoftDocs/fabric-docs · commit 913e606 · +4 −1 lines · also on GitHub
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|July 2026|**Lakehouse Query Explorer (Generally Available)**|[Lakehouse Query Explorer](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Explore-validate-and-iterate-faster-with-the-new-Lakehouse-Query/ba-p/5309466) lets you run Spark SQL in the Lakehouse explorer to inspect data, test joins, create views, and iterate before you move logic to notebooks or SQL analytics endpoints. For more information, see [Query data with the Lakehouse query explorer](../data-engineering/lakehouse-query-explorer.md).|
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|July 2026|**OneLake item-size reporting (Generally Available)**|[OneLake item-size reporting](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Understand-your-data-with-the-OneLake-storage-report-Generally/ba-p/5295144) gives you a workspace storage report that breaks down item data, system data, soft-deleted data, and billing status in the Fabric portal. For more information, see [Get the size of OneLake items](../onelake/how-to-get-item-size.md).|
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|July 2026|**OneLake storage tiers and lifecycle management (Generally Available)**|[OneLake storage tiers and lifecycle management](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Controlling-storage-costs-with-OneLake-lifecycle-management/ba-p/5295135) let you keep active data in the hot tier and move less-used data to cool or cold tiers with lifecycle policies. For more information, see [Get the size of OneLake items](../onelake/how-to-get-item-size.md) and [OneLake diagnostics](../onelake/onelake-diagnostics-overview.md).|
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−| July 2026 | **Planning (Generally Available)** | [Planning in Fabric IQ (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Bring-Enterprise-planning-to-the-AI-Era-with-Planning-in/ba-p/5326315) is a unified no-code platform for collaborative planning, reporting, analytics, data integration, and management. For more information, see [What is planning in Fabric?](../iq/plan/overview.md) |
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+|July 2026|**Dropped warehouse recovery (Generally Available)**|[Dropped warehouse recovery](https://blog.fabric.microsoft.com/blog/dropped-warehouse-recovery-in-microsoft-fabric-preview?ft=All) lets Workspace Administrators restore accidentally dropped warehouses from the Workspace Recycle Bin within a configurable retention window (7 to 90 days), recovering table schemas, data, snapshots, permissions, views, and stored procedures. For more information, see [Manage workspaces](../admin/portal-workspaces.md).|
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+|July 2026| **Planning (Generally Available)** | [Planning in Fabric IQ (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Bring-Enterprise-planning-to-the-AI-Era-with-Planning-in/ba-p/5326315) is a unified no-code platform for collaborative planning, reporting, analytics, data integration, and management. For more information, see [What is planning in Fabric?](../iq/plan/overview.md) |
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|June 2026|**Item Recovery (Generally Available)**|[Item Recovery in Microsoft Fabric (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Item-Recovery-in-Microsoft-Fabric-Generally-Available/ba-p/5240675) lets authorized users restore deleted items across supported workloads through the Workspace Recycle bin or REST API within a configurable retention window of up to 90 days, and admins configure tenant-wide recovery policies from the Fabric admin portal. For more information, see [Retention and recovery in Fabric](../admin/retention-recovery.md).|
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|June 2026|**Operations agent (Generally Available)**|[Operations agent (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Advancing-autonomous-action-with-operations-agent-Generally/ba-p/5192046) is an autonomous agent that monitors your data with Real-Time Intelligence, reasons over your Fabric IQ ontology, and, with your approval, runs pipelines, notebooks, user data functions, and Power Automate flows, with Teams notifications, full tracing and audit, and Microsoft Agent 365 and Microsoft Entra ID governance. For more information, see [Create and configure operations agents](../real-time-intelligence/operations-agent.md).|
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|June 2026|**Diagnose Lakehouse table health with T-SQL (Generally Available)**|[Lakehouse table health diagnostics (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Know-before-you-optimize-Diagnose-Lakehouse-table-health-with-a/ba-p/5228076) add the built-in `sys.sp_get_table_health_metrics` stored procedure to the SQL analytics endpoint, returning anomaly indicators and storage metrics such as small-file counts, deleted-row counts, and checkpoint versions so you can run `OPTIMIZE` only when needed. For more information, see [Optimize Lakehouse tables based on health checks](../data-warehouse/tutorial-conditional-lakehouse-optimization.md).|
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|July 2026|**Usage-based resource estimations (Generally Available)**|[Usage-based resource estimations](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Fabric-July-2026-Feature-Summary/ba-p/5325823#toc-hId--1837831120) help the Fabric Data Warehouse query optimizer use prior execution cardinalities to correct under- and over-estimates for more efficient resource requests and concurrency.|
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|July 2026|**Warehouse source control (Preview)**|By using [Source control with Warehouse (preview)](../data-warehouse/development-deployment.md), you can manage development and deployment of versioned warehouse objects. Use the [SQL Database Projects extension](/sql/tools/visual-studio-code-extensions/sql-database-projects/sql-database-projects-extension) available inside Visual Studio Code. For more information on warehouse source control, see [CI/CD with Warehouses in Microsoft Fabric](https://blog.fabric.microsoft.com/blog/ci-cd-with-warehouses-in-microsoft-fabric/).|
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|July 2026|**Dropped warehouse recovery (Generally Available)**|Workspace Administrators can restore accidentally dropped warehouses from the Workspace Recycle Bin within a configurable retention window (7 to 90 days), recovering table schemas, data, snapshots, permissions, views, and stored procedures. You can [configure the dropped item retention period in the **Item Recovery** tenant setting](../admin/item-recovery.md#set-up-the-retention-period-for-deleted-items).|
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+|July 2026|**Dropped warehouse recovery (Generally Available)**|[Dropped warehouse recovery](https://blog.fabric.microsoft.com/blog/dropped-warehouse-recovery-in-microsoft-fabric-preview?ft=All) lets Workspace Administrators restore accidentally dropped warehouses from the Workspace Recycle Bin within a configurable retention window (7 to 90 days), recovering table schemas, data, snapshots, permissions, views, and stored procedures. For more information, see [Manage workspaces](../admin/portal-workspaces.md).|
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+|June 2026|**GPU-accelerated Fabric Data Warehouse (Early Access Preview)**|[GPU-accelerated Fabric Data Warehouse (Early Access Preview)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/A-new-analytics-frontier-GPU-accelerated-Fabric-Data-Warehouse/ba-p/5191598) uses NVIDIA accelerated computing to run eligible T-SQL queries on GPUs with no query rewrites, delivering up to 7x faster performance at high concurrency across all SQL analytics endpoints and warehouses in a workspace once you enable it from workspace settings.|
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|June 2026|**Bulk Copy API for faster ingestion (Preview)**|[Bulk Copy API (Preview)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Using-Bulk-Copy-API-for-faster-ingestion-in-Fabric-Data/ba-p/5195627) writes data directly to Fabric Data Warehouse tables from application code without first staging files, replacing row-by-row `INSERT` statements to improve ingestion throughput. You can use it through SqlBulkCopy for C#, SQLServerBulkCopy for Java, the [bcp utility](/sql/tools/bcp/bcp-utility?view=fabric&preserve-view=true), and tools such as SSIS, Azure Data Factory, and Informatica. For more information, see [Ingest data into your warehouse by using BCP API (Preview)](../data-warehouse/ingest-data-bulk-copy.md).|
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|June 2026|**Diagnose Lakehouse table health with T-SQL (Generally Available)**|[Lakehouse table health diagnostics (Generally Available)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Know-before-you-optimize-Diagnose-Lakehouse-table-health-with-a/ba-p/5228076) add the built-in `sys.sp_get_table_health_metrics` stored procedure to the SQL analytics endpoint, returning anomaly indicators and storage metrics such as small-file counts, deleted-row counts, and checkpoint versions so you can run `OPTIMIZE` only when needed. For more information, see [Optimize Lakehouse tables based on health checks](../data-warehouse/tutorial-conditional-lakehouse-optimization.md).|
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|June 2026|**New string functions and operators (Preview)**|[New string functions and operators (Preview)](https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/New-string-functions-and-operators-in-Fabric-Data-Warehouse/ba-p/5195232) expand the Fabric Data Warehouse T‑SQL language with **String matching functions** including ([Levenshtein distance](/sql/t-sql/functions/edit-distance-transact-sql?view=fabric&preserve-view=true), [Jaro–Winkler distance](/sql/t-sql/functions/jaro-winkler-distance-transact-sql?view=fabric&preserve-view=true), [Levenshtein similarity](/sql/t-sql/functions/edit-distance-similarity-transact-sql?view=fabric&preserve-view=true), and [Jaro–Winkler similarity](/sql/t-sql/functions/jaro-winkler-similarity-transact-sql?view=fabric&preserve-view=true)), **Concatenation** ( [\|\|](/sql/t-sql/language-elements/string-concatenation-pipes-transact-sql?view=fabric&preserve-view=true) and [\|\|=](/sql/t-sql/language-elements/compound-assignment-pipes-transact-sql?view=fabric&preserve-view=true) ), and **Unicode construction** ([UNISTR](/sql/t-sql/functions/unistr-transact-sql?view=fabric&preserve-view=true)).|
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Microsoft's Markdown source from MicrosoftDocs/fabric-docs, © Microsoft Corporation, under CC BY 4.0. Changed lines with up to 3 unchanged lines around each; ChangeIntel kept this copy 9 Oct 22:05 UTC. The commit date is when the source changed, which can be hours or days before Learn published it.