Join us at FABCON + SQLCON 2027 in Atlanta and save
Planning to join us at FABCON + SQLCON 2027? Register by November 13 to save $300 with early-access pricing, and use code MSCMTY to save an additional $200. Plus, a limited number of buy one, get one (BOGO) offers are available. Ask your account team or Fabric partner to find out how to get one. From March 8–12, 2027, FABCON + SQLCON brings the Microsoft data community together in Atlanta for five days of learning, connection, and hands-on experiences. Two conferences. One registration. FABCON + SQLCON brings together Microsoft Fabric, SQL, and Azure AI in one event. You can mix and match sessions and workshops across both conferences based on the topics most relevant to you. Whether you're exploring Microsoft Fabric, already scaling it in production, building with SQL, or looking at how AI is changing the data landscape, you'll have opportunities to: Hear directly from Microsoft and community experts. Explore expert-led sessions across Fabric, SQL, AI, analytics, data engineering, governance, Power BI, and more. Build practical skills through hands-on workshops. Learn from real-world customer experiences and implementation patterns. Connect with peers, Microsoft product experts, partners, and the broader data community. Register by November 13 to save Take advantage of early-access pricing before it ends: Save $300 by registering by November 13. Save an additional $200 with discount code MSCMTY. Ask your account team or Fabric partner about a limited number of available BOGO offers. FABCON + SQLCON 2027 March 8–12, 2027 Atlanta, Georgia Register today and start planning your FABCON + SQLCON 2027 experience.
My workspace governance improvements (Generally Available)
My workspace governance features, which give administrators governance controls over their users' personal My workspaces, are now generally available. As My workspaces continue to be used for business-critical content, organizations need governance capabilities that scale with their environment. These enhancements give administrators greater flexibility to access, manage, and recover content when needed, while enabling automation that reduces operational overhead and improves consistency across the tenant. These enhanced tenant administrator controls for My workspace are also available in government clouds. What's new Two new admin REST APIs make temporary admin access to a personal workspace fully programmable: Grant Admin Temporary Access: grants a Fabric administrator 24-hour access to a user's My workspace. Remove Admin Temporary Access: revokes that access before the 24-hour window ends. Both can be called by a Fabric administrator or by a service principal. The service principal identity must be enabled for Admin API access in your tenant settings. SPN support and these new APIs allow tenant administrators to automate management of tenant users’ My workspaces contents instead of doing it by hand in the Admin Portal. Reminder: Restoring orphaned My workspaces When a user is hard deleted in Microsoft Entra, their My workspace becomes orphaned and moves to a Deleted state, with contents retained for 30 days. During that window, you can restore it with the Restore Workspace API. Important: new workspace name is required when restoring a former My workspace, and you assign a new admin to own the recovered content. Try the Admin controls and new APIs and let us know what you think in the comment section.Power BI September 2026 Feature Summary
As the Power BI, Microsoft Fabric, data, and analytics community gathers in Barcelona for the European Microsoft Fabric + SQL Community Conference, this month is packed with news. From new Copilot and AI experiences to reporting, modeling, data connectivity, developer enhancements, and mobile updates, we're sharing the latest innovations designed to help you build, analyze, and act on your data more effectively. Whether you're joining us in person or following along from afar, this roundup is your guide to everything new across Power BI this month. General Deprecation of Old File Picker experience in Power BI Desktop In April we deprecated the old file picker experience in Power BI Desktop. Starting in October, users using versions of Power BI Desktop from March 2026 or earlier will no longer be able to save and share Power BI files to OneDrive and SharePoint. Please ensure you update Power BI Desktop to keep using this functionality. Copilot and AI Power BI Agentic Experiences (Generally Available) Agentic development in Power BI is real, and it is already delivering value: whether you are starting from scratch with greenfield projects or building upon existing solutions in brownfield scenarios, BI developers can delegate the work to an agent, review the result, and refine it rather than starting from scratch every time. What makes this work is tools and context. Through Work IQ and Fabric IQ, the agent grounds its work in your business context—your data, your semantics, and the way your organization operates. Through skills—published by Microsoft in skills-for-fabric, shared by the community, or personalized by your own team—it also picks up your development context: the modeling and reporting practices, conventions, and workflows your team expects. Through tools such as the Power BI Authoring MCP server and the Power BI Desktop Bridge CLI, the agent can act on that context: reading and changing semantic models and reports directly, reloading its edits in Power BI tools, and reviewing its own work. Point an agent at a requirements document or a screenshot of the layout you want, describe what you need, and the agent can help accelerate the initial authoring pass, which you can then review and refine. rt authoring skills. What's available today The powerbi-authoring plugin in microsoft/skills-for-fabric bundling the semantic modeling and reporting agent skills and tools. It was recently updated to support report authoring for remote semantic models in Power BI service and an expanded range of supported report visuals, including custom visuals. To learn more, refer to the Power BI skills documentation. The local Power BI Authoring MCP server allows the agent to edit semantic models in Power BI Desktop. To learn more, refer to the Power BI Authoring MCP documentation. Power BI Desktop Bridge lets an agent reload changes in a running instance of Power BI Desktop and capture screenshots to check its own work. To learn more, refer to the Power BI Desktop Bridge documentation. Browser-based validation for remote report editing, so the agent can validate a report using a headless browser (an automated browser that runs without a visible user interface). Removing the local Power BI Desktop dependency allows the full authoring loop to run without Power BI Desktop, extending the agentic experience to Mac users and others who do not rely on a local installation. To learn more and get started, refer to the Power BI agentic documentation. Microsoft 365 Copilot is coming to Power BI (Preview) Copilot experiences have emerged across the applications people use every day, bringing AI closer to the work happening in each product. But this can also feel fragmented, with different entry points, separate conversations, and uncertainty about which Copilot agent to use. Our goal is to create a consistent Copilot experience that is available wherever people work. People should not have to leave the application they are using to find it. Microsoft 365 Copilot should be available within their experience, carry relevant context across experiences, and connect to the specialized intelligence of each product. We’re taking an important step toward that goal with a preview of Microsoft 365 Copilot integrated directly into Power BI and Microsoft Fabric. This integration gives users a familiar place to bring together business context and trusted data. Shared conversation history lets them continue a discussion as they move between Microsoft 365 Copilot experiences instead of starting over in each application. ower BI experience, including integration with Work IQ. In Power BI, a question no longer has to stop with the numbers in a report. A sales leader could use Fabric IQ to identify which regions are behind plan, then use Work IQ to connect the results with customer emails, meetings, account plans, and documents. They could summarize the complete picture and even kick off actions and tasks in Cowork, all from inside Power BI. This work context and ability to move directly from insight to action were not available in the standalone Power BI Copilot experience. the Cowork integration into the Power BI experience, highlighting the full Microsoft 365 experience embedded into Power BI. A new setting in the Fabric admin portal will determine whether this integration is available by enabling or disabling its entry point in the navigation pane. It will be off by default, giving administrators time to evaluate the experience before introducing it to their organization. Administrators can enable it when they are ready and disable it if they need to pause access. This setting is independent of the existing setting for standalone Power BI Copilot. If both settings are enabled, users with a Microsoft 365 Copilot license will see entry points for both experiences, and standalone Power BI Copilot will continue to appear on Home. If standalone Power BI Copilot is disabled and Microsoft 365 Copilot is enabled, users will see only the Microsoft 365 Copilot entry point. During the initial preview, the integrated experience is available only to users with a Microsoft 365 Copilot license. These users receive the full Copilot Chat experience in Power BI and Fabric, bringing together Fabric data through Fabric IQ and relevant Microsoft 365 context through Work IQ. Existing permissions and governance controls continue to determine which content each user can access. Support for a broader Fabric audience will follow. This expansion will give Fabric users without a Microsoft 365 Copilot license access to an integrated Copilot experience tailored to their available capabilities. The experience may differ from the full licensed offering, but it will extend Fabric IQ and conversational data experiences to more types of Fabric users. The preview will roll out with the setting turned off by default, with administrators choosing when to enable it for their organization. This is an important step toward one Copilot that meets people wherever they work, connecting the context surrounding each decision with trusted business data. To learn more, refer to the Copilot in Power BI documentation. Power BI data answers in Microsoft Copilot Chat (Generally Available) Users can find and ask questions about Power BI reports and semantic models directly from Microsoft 365 Copilot. They can search for relevant Power BI content, attach a report or provide a link, and ask questions in natural language. Powered by Fabric IQ, the experience uses the data, measures, relationships, and business logic already defined in Power BI to provide grounded answers. Users can also bring Power BI insights into conversations that include their Microsoft 365 work context, such as emails, meetings, and documents. Microsoft 365 Copilot now supports Microsoft Purview Data Loss Prevention (DLP) policies and information protection controls for this experience. This helps organizations adopt conversational analytics while applying their existing policies for identifying, classifying, and protecting sensitive data. The experience continues to respect existing Power BI permissions and Microsoft 365 governance controls. Users can only access Power BI content they are authorized to view, and administrators retain control over whether Fabric data is available in Microsoft 365 Copilot. Organizations can use Power BI data answering in Microsoft 365 Copilot with production support and service commitments. This milestone makes it easier for users to bring trusted business data into the flow of work without leaving Microsoft 365 Copilot or creating a separate agent. To learn more, refer to the Fabric IQ in Microsoft 365 Copilot Chat (Frontier) documentation. Fabric IQ Plugin in Microsoft 365 Copilot Cowork (Generally Available) Power BI data is available where multi-step work happens, so a business question, the analysis behind it, and the follow-up it triggers stay in one place. To ground a task in Power BI, users can search for relevant content, attach a report, or paste a link to a report or semantic model. Questions are answered using the data, measures, relationships, and business logic already defined in the semantic model. Coverage now extends to reports published through organizational apps, with improvements to content discovery, large model handling, schema selection, Verified Answers, and row-level value search. The plugin also carries forward the governance controls organizations rely on in Power BI: Existing access controls: Power BI permissions and row-level security determine which reports and semantic models each user can reach. Citations and sensitivity labels: Responses cite the Power BI content behind an answer and surface the Microsoft Purview Information Protection label applied to it, so users can see where a number came from and how it is classified. From insight to action: With Fabric IQ, users can analyze Power BI reports using natural language, uncover key findings, and put those findings to work right away in Cowork. Whether they are summarizing business performance, investigating a trend, or answering a data question, Fabric IQ turns trusted organizational data into outcomes. To learn more about supported scenarios, setup, and current considerations, refer to the Fabric IQ in Microsoft 365 Copilot Cowork documentation. For licensing and pricing information, refer to Microsoft 365 Copilot plans and pricing. Build Fabric Apps more easily in GitHub Copilot App (Preview) Fabric Apps were introduced in June as an AI-first way to build custom web apps with Microsoft Fabric as the backend. This month we’re excited to share that building these Fabric Apps on your governed data has become even easier with the GitHub Copilot App, which gives you a natural language chat interface instead of a command-line interface. . To try it out, start by downloading the GitHub Copilot App. Then navigate to Customize > Plugins > Rayfin, and select Install to enable our dedicated plugin: Rayfin plugin in GitHub Copilot App. Once the plugin is enabled, simply start a new chat and work with Copilot to help plan your Fabric data app. After you review and approve the plan, ask the agent to execute it and specify the workspace where you want to deploy the app. . We look forward to seeing the amazing apps you build! Check out our community gallery for inspiration. Enhanced Report Consumption Copilot with Fabric IQ When viewing a Power BI report, you can enable Fabric IQ from the Copilot pane to better answer complex questions about your data. This enhancement merges existing Fabric IQ capabilities into Power BI Copilot report viewing mode, allowing Copilot to use a multi-step approach to evaluate data in the semantic model and refine its approach when generating a response. . With Fabric IQ enabled, Copilot can: Provide better answers to questions about your data based on detailed reasoning capabilities directly into the report viewing experience. Show reasoning steps to help you understand how Copilot provided an answer. Generate Fabric visuals to help you further analyze your data. Answers can include column, bar, stacked, line, area, pie, donut, scatter visuals. Provide the underlying DAX query and data table used to generate a response. . To learn more, refer to the Ask Copilot questions about your data documentation. New control for Copilot access to semantic models Power BI now provides semantic model editors with greater control over how Copilot can be used with their data. Users with write permissions can block read-only users from accessing a semantic model through Copilot and Microsoft’s remote MCP tools, supporting governance, compliance, and access-control requirements. The setting applies across Copilot experiences that query the semantic model, including Power BI Copilot experiences; Microsoft 365 Copilot Chat and Cowork; and data agents, remote Fabric MCP servers, and Power BI MCP servers. When disabled, users with read-only access won't be able to access that semantic model through these experiences. By default, the setting remains enabled to preserve the current behavior. This setting appears in the Copilot section with the following description: “Allow any person with read-only access to use AI (i.e. Copilot, Microsoft’s MCP tools) on the model and its related reports.” Setting that allows people with read-only permission to use AI experiences with the semantic model and its related reports. This update gives organizations a clear and enforceable way to control AI access to semantic model data while maintaining flexibility for semantic model editors. To learn more, refer to the Use Copilot with Semantic Models in Power BI documentation. Remote Power BI Authoring MCP Server (Preview) The Power BI Authoring MCP enables AI applications to create and modify semantic models in Fabric workspaces, without installing or maintaining anything local. This release also unblocks Mac users that want to use the Power BI Authoring MCP, because the server runs remotely and does not require local binaries. Use the following endpoint in AI applications such as GitHub Copilot App: https://api.fabric.microsoft.com/v1/mcp/powerbi/authoring The local Power BI Authoring MCP server, released in November 2025, remains generally available. It remains an option when an agent needs to work with Power BI Desktop, Power BI Project (PBIP) or TMDL files on disk. The local and remote servers support the same authoring capabilities. We recommend using the remote server when local development is not required, such as when creating a Direct Lake semantic model in a Fabric workspace. In the following example, the AI agent uses one tool call to create a Direct Lake semantic model connected to a Fabric Lakehouse: To learn more, refer to the Power BI Authoring MCP server documentation. Reporting New Report Ribbon on the web (Preview) The Report ribbon is now available on the web, providing a consistent experience for report consumption and authoring that more closely matches Power BI Desktop. The ribbon organizes commands into clear, easy-to-navigate tabs, making it easier for users to discover features, interact with reports, and complete editing and authoring tasks directly in the browser. It also introduces the new Design ribbon and additional capabilities that were previously unavailable on the web, such as Format Painter. This milestone brings greater consistency to Power BI report-authoring experiences and marks an important step toward a seamless, end-to-end reporting workflow on the web. As web authoring capabilities continue to expand, users will be able to accomplish more of their reporting tasks directly in the browser, enabling a more streamlined, productive workflow. Enable the Try the new ribbon (preview) at the top of the page to explore the new experience. You can disable the setting to return to the previous ribbon. To learn more, refer to the Report Ribbon on the web documentation. Live Visual Sharing in Outlook on the web (Preview) For years, sharing data through email has been stagnant. You could send a screenshot, but it immediately became stale. You could attach a report link, but recipients had to leave their workflow to find the context they needed. And every follow-up question often meant another screenshot, another export, or another email thread. Now, we're bringing a new way to share Power BI insights directly in the flow of work with Live Visual Sharing in Outlook. With Live Visual Sharing, you can insert a Power BI visual into Outlook on the web and share it as a live, interactive experience. Recipients can view and interact with the visual directly in Outlook while staying connected to the latest underlying data. When a live visual is shared, Outlook renders an interactive version of the Power BI visual. Rather than embedding a static image, the experience remains connected to the source report and retrieves current data when viewed. Recipients can: Interact with the visual directly in Outlook on the web. Access tooltips and explore data points. See filters and slicers applied at the time of sharing. View refresh information and data context. Navigate back to the source report when deeper analysis is needed. The result is a richer conversation around data, directly within Outlook. Sharing a live visual is simple: Open a Power BI report in the service. Select a visual to share, then select More options in the upper-right corner. Select Share. Select Link to this visual. A pop-up will appear asking if you want to use the current view (apply existing filters and slicers) or not. After selecting Create Link, the link is copied to your clipboard. Open Outlook on the web. This experience is not available in the Outlook desktop app. Create a new email. Paste the link in the email. The visual renders in loop after a few seconds! You can also share the same link in a Loop page, and the visual will also be rendered. By combining Power BI, Outlook, and Loop-powered experiences, we're bringing data closer to where collaboration happens. Live Visual Sharing can support more informed, data-driven conversations in Outlook. To learn more about Live Visual Sharing in Outlook, refer to the Share live Power BI visuals documentation. More control and context in Power BI Home (Generally Available) Power BI Home now provides additional context and personalization options to help users discover the right content more efficiently. With new freshness indicators and customizable list views, you can quickly identify the most relevant reports and semantic models, prioritize the metadata that matters most, and tailor the experience to fit your workflow. Find the right content more easily Discover the right content more easily with new Data Refreshed and Modified Date columns in Power BI Home. By bringing the freshness signals already familiar from workspace list views into Home, users can more easily spot recently updated reports and semantic models, distinguish between similar items, and quickly find the content that matters most. Whether you're checking for the latest business updates or deciding which refreshed report to open, you can navigate with greater confidence and less guesswork. Customize your Home list view Not every user, team, or organization relies on the same signals to discover content. With Column Options, you can show or hide metadata, drag and reorder columns to prioritize the information you use most, and reset to the default view at any time. Whether you rely on freshness signals, endorsements, sensitivity labels, or location information, you can tailor Home to match your workflow. To learn more, refer to the Power BI Home documentation. Set and reset column widths in table and matrix (Generally Available) You can now right-click a column header in a table or matrix and select Set column width to specify its width in pixels. This option helps report viewers improve readability and fit the information they need within the available space, without changing the report author’s design or affecting other viewers. Changes made by viewers last only for the current viewing session. To restore the width defined by the report author, right-click the column header and select Reset column width. To learn more, refer to the Adjust column width in Power BI tables documentation. Visual calculations for small multiples (Generally Available) You can now use visual calculations in visuals with small multiples. Create calculations such as moving averages and compare trends across categories without adding separate measures to the semantic model. In the visual matrix, the field in the small multiples field well appears on the ROWPAGES axis. You can select ROWPAGES by itself or combine them with ROWS and COLUMNS to control how the calculation moves through the visual. e: Create a moving average visual calculation for a line chart divided into small multiples by country. To learn more, refer to the Visual calculations overview documentation. Design ribbon for Power BI reports (Generally Available) The new Design ribbon brings report styling tools together in one location. Apply a built-in or organizational theme, open the Theme pane to customize report-wide defaults, or import and download theme files directly from the ribbon. You can also quickly open Page size, Page background, and Wallpaper settings for the current page. Two new built-in themes, Dark and Soft dark, use the new Versa color palette and styling that closely follows the Fluent 2 base theme. These themes let you design against a dark report canvas and return to the default light theme before publishing if needed. To learn more, refer to the Use the Design ribbon in Power BI documentation. Slider color options for Slicer visual (Generally Available) Match your slicer's slider to your report design. The Slicer visual's Between, Before, After, and Date picker settings include a Slider format section where you can turn the slider on or off, set the handle style, and choose colors for the handles, selected range, and track. Handle options adjust based on the Responsive layout toggle (General > Properties > Advanced options). When Responsive is on, handles appear as circles with Fill color, Border, and Size. When Responsive is off, handles appear as rectangular bars with Border, Width, and Height. To learn more, refer to the Slicer visual in Power BI documentation. Translytical task flows show user date function (UDF) information in button action (Generally Available) The formatting pane now displays the Workspace, Function set, and Data function assigned to a data function button. These read-only details help you confirm that the button references the intended function without reopening the OneLake catalog. This information is especially useful when you review or troubleshoot reports that use several functions or connect to functions across multiple workspaces. To learn how to configure data function buttons, refer to Create a data function button in Power BI. Format pane headers stay visible as you scroll (Generally Available) Expanded section headers now remain visible at the top of the Format visual pane as you scroll through their settings. This update helps you keep track of the section you’re editing, especially when a section contains many formatting options. For example, when you scroll through color settings, the Colors and Data colors headers remain visible for context. To learn more about formatting visuals, refer to Get started formatting report visualizations. Pick the axis initial scroll position (Generally Available) Categorical axes—like month, year, or product name—show a scrollbar when there are more categories than fit in the visual. Until now, the scrollbar always started at the beginning of the data, so the oldest values displayed first. This month, you can set Initial scroll position to End on the axis Layout section, and the visual loads with the most recent data in view. Users can still scroll back to see earlier history. The option is available on stacked, clustered, and 100% stacked bar and column charts; line, area, stacked area, and 100% stacked area charts; line and stacked column and line and clustered column charts; ribbon, waterfall, and scatter charts with a categorical X-axis. Initial scroll positionset toEndon the X-axis. The scrollbar is positioned on the right, showing the most recent months first. To learn more, refer to the Customize x-axis and y-axis properties documentation. Azure Maps geocoding improvements (Generally Available) Large reference layers now render correctly when you filter your report. Reference layers add geographic context using points, lines, and polygons, such as locations, routes, postal codes, sales territories, and administrative regions. The Azure Maps visual renders up to 30,000 reference-layer features at a time. Previously, when a reference layer exceeded this limit, features excluded from the initial view could remain missing even after a report filter narrowed the data to a smaller area. . . . Now, Azure Maps re-evaluates the reference-layer features whenever report filters are applied. The unfiltered view is still limited to 30,000 features, but a filtered view accurately displays the relevant features, up to that limit. On-object interaction improvements (Preview) Based on your feedback during preview, we're introducing the first in a series of on-object interaction improvements, designed to make quick edits to your visuals easier. This month we're refining how you add data and manage some visual elements. The Build flyout now opens only when you select Add data, helping you stay focused when dragging and dropping data directly onto a visual or into the Build pane. We’ve also separated Title and Subtitle in the Add to your visual flyout, so you can manage them independently. In addition, title and subtitle are now turned off by default for matrix, table, and card visuals in reports that use the latest base theme. New reports automatically use the latest base theme. For existing reports, select Update theme in the Theme pane to apply this change. You can turn either element back on when needed. to your visual menu. To learn more, refer to the using on-object interaction with visuals and updating to the latest base theme documentation. Support for Fabric Apps in Org apps (Coming Soon) Soon, users will be able to include generative Fabric Apps alongside the reports, dashboards, notebooks, and other content in your Org Apps. For example, imagine you want people to rate the content in an Org App and share feedback about what would make it more useful. You can create a Fabric App for that experience and add it directly to the Org App. Whether you’re helping people explore what could happen next, act on an insight, or complete a specialized workflow, Fabric Apps give you a flexible new way to build for your audience without sending them somewhere else. Together, organizational apps and Fabric Apps provide a way to bring enterprise reporting, content, and tailored experiences together for your organization. Learn more about org apps and item types supported, including Fabric Apps. Changes to Power BI subscription email delivery Power BI is updating the platform used to deliver subscription emails as part of ongoing improvements to delivery reliability and long-term service health. As eligible subscriptions move to the updated platform, customers may notice changes to the sender identity and email formatting. Each subscription transfers automatically when it moves. Customers do not need to recreate it or change its schedule or recipients. After selecting Subscribe for an item, an information icon identifies a subscription that has moved to the updated email delivery platform. Learn more about changes to Power BI subscription emails. Increased Export to Excel row limits (Coming Soon) Many users export Power BI data to Excel for further analysis. This month, we're increasing the maximum number of rows that can be exported from table visuals using Data with current layout from 150,000 to 500,000. This increase helps you analyze larger datasets in Excel with fewer export operations. s. To learn more about exporting data from Power BI visuals, refer to Export data from a Power BI visualization. Value selection in Narrative visual We are replacing the Q&A natural language experience for creating dynamic values in the Narrative visual and text box with a more deterministic UI. This is due to the ongoing deprecation of the Q&A tool, and also based on feedback that it was hard to deterministically pick exact values through the Q&A experience. Authors can now create and edit custom values through a direct, deterministic UI: select a column or measure, apply any valid summarization, and add any type of filter. Auto-generated values are unchanged, and values previously authored with Q&A remain available as read-only. To learn more, refer to the Create Smart Narrative documentation. Modeling Create and edit DirectQuery semantic models in the Power BI service DirectQuery semantic models can now be created and edited directly in the Power BI service, eliminating the need to download and use Power BI Desktop. Previously, building models that query data sources in real time meant downloading Desktop, authoring the model, and publishing it to the web. Now, web-based modeling gives your team the freedom to: Work from any device: Mac, Linux and Windows users can now author DirectQuery models straight from the browser. Collaborate in real time: Multiple team members can work on the same semantic model simultaneously. Ditch the desktop loop: Skip the download-edit-republish cycle and update your models instantly in the service. Capabilities on the web Start from scratch: Connect to a supported data source and choose DirectQuery mode. Figure: Power Query interface displaying data source connection settings, with DirectQuery selected as the data connectivity mode. Full modeling control: Open existing DirectQuery models to manage relationships, write DAX and tweak table/column properties. : Model View in Power BI Service showing tables, relationships, and the properties panel for editing a DirectQuery semantic model. Flexible storage modes: Easily switch table storage modes from DirectQuery to Import or Dual if needed. : Properties pane that allows user to switch table storage modes from DirectQuery to Import or Dual. Thanks to this new capability, composite models are also available on the web! Head to the Power BI service and open one of your DirectQuery semantic models or create a brand-new one. We'd love to hear what you think! Learn more in the DirectQuery documentation. Approximate Distinct Count comes to Import and Direct Lake (Preview) Distinct count is one of the most resource-intensive operations in any analytical engine. As data cardinality grows, so do CPU and memory usage, often slowing down your interactive reports. APPROXIMATEDISTINCTCOUNT already offered a faster alternative for DirectQuery sources such as Azure SQL, Synapse, BigQuery, Databricks, and Snowflake. This month we're extending support to Import, Direct Lake on OneLake, and Direct Lake on SQL semantic models. DAX = APPROXIMATEDISTINCTCOUNT(<columnName>) : Model View in Power BI Service showing tables, relationships, and the properties panel for editing a DirectQuery semantic model. How it works and when to use it Instead of scanning every single unique value, APPROXIMATEDISTINCTCOUNT calculates a highly accurate estimate of unique values with a standard error rate of ~1.6%. In return, you get faster query execution times. Best for high-cardinality columns: Use it on columns with millions of unique values (such as transaction IDs, user IDs, or timestamps) where an approximate result can reduce the resources required to calculate distinct values. Keep standard DISTINCTCOUNT for low-cardinality data: Stick to exact counts for smaller attributes like Country, Category, or Status, where standard calculation is already fast, or for financial metrics where absolute precision is required. Swap APPROXIMATEDISTINCTCOUNT into your heaviest measures today and let us know how much speed you gain on your models! Learn more in the APPROXIMATEDISTINCTCOUNT documentation. Accelerate text searches in your semantic models with String Indexing (Preview) String Indexing for Power BI semantic models is coming soon! If your reports rely heavily on text fields, such as product names, customer comments, or long descriptions, you’ve likely faced slow performance when users search or filter on large semantic models. String Indexing is designed to improve text-search performance in supported semantic models. Why String Indexing? Common text operations like DAX functions (SEARCH(), CONTAINSSTRING()) and advanced text slicers in reports traditionally scan data row-by-row. As datasets grow, these scans slow down query times. String Indexing builds specialized indexes so the engine can locate matching text more efficiently, which can improve report responsiveness for both Import and Direct Lake semantic models. Indexing modes You can configure String Indexing via model metadata to fit your workload needs: Auto Mode: Automatically builds the index on the first query execution for a qualifying column. The index does not persist in storage; it remains in memory only while the column is loaded and will be rebuilt on subsequent queries if evicted. Ideal for smaller models. Full Mode: Builds and persists the index during scheduled data refreshes. While refresh times and model size may slightly increase, users enjoy consistently fast query performance right out of the box. Get started String Indexing requires a semantic model running at 1707 compatibility level. During this initial preview phase, indexing can be configured through TMDL on the web or XMLA metadata. Desktop support and a dedicated UI experience within Power BI are planned for a future release to simplify setup. Check out the String Indexing documentation for setting up instructions, prerequisites, and guidance on choosing the right indexing mode for your models. We look forward to seeing how this feature helps make text-heavy reporting experiences faster and more responsive! Introducing Full-Text Search in Power BI Semantic Models (Preview) Full-Text Indexing for Power BI semantic models is coming soon! While traditional string searches look for exact character matches, Full-Text Indexing enables a more intelligent search experience based on the meaning of words and natural language concepts. This capability powers two new DAX functions, TEXTCONTAINS() and TEXTSIMILARITY(), making it easier than ever to analyze large volumes of textual data directly in your semantic models. Why Full-Text Indexing? Business data increasingly contains rich text content such as customer feedback, support tickets, product descriptions, incident summaries, and knowledge articles. Searching this data using traditional string matching often requires exact matches and can miss relevant results due to differences in spelling, word forms, or phrasing. Full-Text Indexing builds a specialized search index at the column level, allowing semantic models to understand words rather than just character sequences. This enables advanced search experiences such as: Finding related words through linguistic analysis (for example, run, running, and runs) Matching singular and plural variations automatically Ignoring common stop words such as "the" or "and" Supporting phrase-based searches Tolerating minor spelling mistakes through fuzzy matching Enabling semantic similarity search scenarios Getting Started FTS Indexing requires a semantic model running at 1708 compatibility level. During this initial preview phase, indexing can be configured through TMDL on the web or XMLA metadata. Desktop support and a dedicated UI experience within Power BI are planned for a future release to simplify setup. New DAX functions Full-Text Indexing is required for two new DAX functions: TEXTCONTAINS() Returns TRUE when a text value matches a search expression using full-text search semantics rather than simple substring matching. It supports multiple search modes, including keyword matching, phrase matching, and fuzzy matching for typo tolerance TextContains(<WithinTextColumn>, <SearchText>, [MatchMode]) Example: "Show me all reviews that mention spa." The review either matches or it doesn't. TEXTSIMILARITY() Returns a relevance score indicating how well the text in <WithinTextColumn> matches <SearchText>. It enables similarity-based text comparisons, helping identify records that are semantically related even when they do not contain the exact same words. TextSimilarity(<WithinTextColumn>, <SearchText> [, <MatchMode>]) Example: "Show me the 10 reviews most relevant to 'good breakfast'." Reviews mentioning both terms prominently rank higher than reviews that only partially match. Learn more about these two new DAX functions (TEXTCONTAINS, TEXTSIMILARITY) in our documentation. Full-Text Indexing is supported for both Import and Direct Lake models, with Full mode recommended (during Preview) for the best out-of-the-box performance and user experience. Refer to the Full Text Indexing documentation to learn more about prerequisites, configuration options, and setup instructions. Data connectivity New Power Query editor (Preview) Since May of this year, the modern Get Data experience has been available in preview inside Power BI Desktop; the feedback we've gathered from that rollout has directly shaped what comes next. Your reports of friction points, missing capabilities, and rough edges between the legacy and modern interfaces went straight into the backlog, and this month that work pays off: the full modern Power Query Editor experience moves into preview. It's the same trusted engine, wrapped in a completely refreshed editing surface — and we're still closing the remaining gaps with the legacy UI as we go. Let's explore six key reasons to enable and try this feature. Modern Get Data - The same connector browsing and search experience you already know from Fabric Dataflow Gen2 — now in Desktop. Searchable, categorized, and designed to make connectors easier to find and navigate than the legacy dialog. Try it: Connect to a new data source and browse the OneLake catalog. To learn more, refer to the Data sources in Power BI Desktop documentation. Dark theme, end to end - No more jarring light-mode panes breaking your flow. The legacy editor only partially supported dark theme. The modern editor applies it consistently across the preview grid, dialogs, and other parts of the editing surface. Folding visibility - Stop guessing whether your query folds. Step folding indicators mark each step as folding or not, and the new query plan shows exactly how the engine intends to evaluate your query — and where folding breaks down. Try it: Open the query plan on a query with several steps and find where folding stops. To learn more, refer to the Understanding Query Evaluation and Query Folding in Power Query documentation. Diagram view - See how your queries relate to each other visually, instead of reverse-engineering it from names. A gamechanger for files you've inherited or models with long reference/merge chains. Try it: Open a file with referenced queries and trace a merge visually. To learn more, refer to the Diagram view documentation. New capabilities, now on Desktop - Features that used to live only on the web are now here: rank column, cluster values, schema view, query script view, plus upgrades to transforms you already use daily. Try it: Add a rank column or cluster values on a messy text column. To learn more, refer to the Rank column and Use Schema View documentation. Export a Power Query template - Capture your solution at a point in time and take it with you. Export a template from Desktop and import it straight into a Dataflow Gen2 — queries, steps, and structure intact. Try it: Export a template from a multi-query file and import it into a Dataflow Gen2 to compare. Figure: Screenshot of the Export template experience in the Power Query editor. To learn more, refer to the Power Query template documentation. Ready to try it? Enabling the modern Power Query experience takes just a few seconds — no restart required: Open Power BI Desktop. Locate: File > Options and settings > Options. Under Preview features, check New Power Query experience. Open (or reopen) the Power Query Editor — you're now in the modern experience. Once you've had a chance to explore this new user interface and its experiences, we want to hear from you. Share your thoughts on the new Power Query experience in the Fabric Community — what's working, what's missing, and what would make it a compelling alternative from the legacy editor. Every comment helps shape what ships next. Microsoft Outlook Mail connector (Preview) We're introducing the new Microsoft Outlook Mail connector (Preview) for Power BI Desktop. Built on the Microsoft Graph API, it lets you read your mailbox data — folders, messages, and attachments — using an organizational account. This is the first in a set of new connectors we'll be releasing as a modern alternative to the Exchange Online connector. The initial preview is scoped to Mail in Power BI Desktop. Additional connectors for Calendar Events, Contacts, and Tasks are on the roadmap, along with Excel and Power BI service / Fabric Dataflows Gen2 support. Scheduled refresh isn't supported yet — this applies to both the Power BI service and refreshes routed through the on-premises data gateway. To try it, enable the Microsoft Outlook Mail preview feature under Options in Power BI Desktop, then open Get Data → Online Services → Microsoft Outlook Mail and sign in with your organizational account. To learn more, refer to the Microsoft Outlook Mail connector documentation. More flexible Data Privacy Firewall query patterns in Power BI Desktop (Preview) Power BI Desktop now allows Data Privacy Firewall partitions that reference other partitions also access data sources when the privacy levels of the involved data sources are compatible. Introduced in the July 2026 release and enabled by default, this preview setting aligns Power BI Desktop with Power Query Online, gateways, and the Power BI service. This change supports common query patterns in which one query returns a value that another query uses to build a web request, SQL statement, file path, or other data source request. These patterns can now run without refactoring queries or duplicating logic solely to satisfy the previous partition restriction. The Data Privacy Firewall remains active. Power Query continues to evaluate the privacy levels of the involved data sources before combining data, helping authors use more flexible query designs while preserving privacy protections. To learn more, refer to the Allow data privacy firewall partitions that reference other partitions to also access data sources documentation. Mobile Mobile page indicator (Generally Available) Know immediately which report pages are mobile-ready, without clicking through them. Each page that has a mobile layout shows an icon on its page tab in the footer, so you can spot your mobile coverage instantly. Pages without a mobile layout stay unmarked, making it easy to see what's left to optimize. The icon is coming soon to both Power BI Desktop and the Power BI service. In Power BI Desktop, it appears in both desktop layout view and mobile layout view, so you can track mobile coverage right where you work. In the Power BI service, it appears in mobile layout view. Page tabs marked with an icon to show which pages have a mobile layout. To learn how to build mobile-optimized reports, refer to the Mobile-optimized Power BI reports overview documentation. Contact details in Info drawer (Generally Available) We’re making it easier to connect with the right people from the Power BI Mobile app. You can now find contact details in the Info drawer for reports, apps, and dashboards, and email the relevant contact directly from your phone. To learn more about Power BI in mobile, refer to the What Are the Power BI Mobile Apps? documentation. Developers and APIs Power BI Projects (PBIP) (Generally Available) Since entering preview in 2023, PBIP has changed how developers build and manage Power BI content. It stores report and semantic model definitions as human-readable text files, turning a Power BI solution into a codebase. Developers can search these files, track changes in Git, review diffs in pull requests, automate updates with scripts and pipelines, and use AI agents to work with models and reports. Changes remain visible and reversible, which makes team development easier and safer. Recent improvements have made the workflow more practical. These include opening a project directly in Visual Studio Code and detecting external file changes in Power BI Desktop. New underlying formats capabilities: Tabular Model Definition Language (TMDL) for semantic models. Power BI Enhanced Report Format (PBIR) for reports. PBIR is now the default report format for PBIX and PBIP files. New reports use it from the start. When you edit a report that uses the legacy format, Power BI tools automatically convert it to PBIR. To learn more, refer to the Power BI Projects documentation. New Purge Data option for Fabric APIs The new Purge Data option for Fabric APIs gives developers and administrators greater control over programmatic semantic model deployments. This capability allows users to explicitly approve deployments that may require removing existing data, helping unblock scenarios such as schema or data type changes that previously failed validation checks. Designed with both safety and automation in mind, purgeData keeps data protection safeguards enabled by default while giving developers the flexibility they need to manage complex deployment scenarios at scale. To learn more, refer to the Purge Data documentation. Other Data updated and sensitivity fields of Power BI report in Microsoft Teams preview card (Coming Soon) Power BI report previews in Microsoft Teams will soon surface the report's last refresh date and sensitivity label. These additional signals will help users quickly assess the freshness, relevance, and classification of a report before opening it. To learn how Power BI content is displayed in Microsoft Teams, refer to the Link preview cards in Microsoft Teams chats and channels documentation. Artifact info header for Power BI tabs in Microsoft Teams (Generally Available) Power BI content in Microsoft Teams tabs now includes the artifact info header, giving users the context they need without leaving their flow of work. Available for reports, apps, organizational apps, dashboards, and scorecards, the header brings key artifact information and actions together in one place. The new header displays the artifact name and sensitivity label and provides an entry point to artifact metadata. You can open the artifact in the Power BI personal app in Teams, open it in a browser, and refresh the tab. Tab owners can control their experience with the new Show info header setting on the tab settings page. The setting is 'on’ by default and can be turned off when a more compact tab experience is preferred. To learn how to add Power BI content as a tab in Microsoft Teams, refer to the Embed Power BI reports in Microsoft Teams documentation. Third-party custom visuals graphomate matrix The graphomate chartrix is a brand-new charting visual, and it offers various improvements over graphomate charts. First and probably most obvious is the new interactive user interface which enables users to define most elements of the chart layout directly on the visual. To keep this interface effective and uncluttered it focuses on the most important parameters of your chart. Users can now create combination charts which were simply not possible before. There are also new chart types like the variance waterfall, which automatically renders from one measure and two dimensions. Of course, the graphomate chartrix is IBCS® certified. With the latest release an XFL editor has been introduced, which helps you write scripts to format the chartrix far beyond the possibilities of the regular option set. XFL scripts also provide a way to conditionally format the visualization, dynamically changing properties in relation to the actual data. This new visual is provided free of charge to existing customers of the graphomate charts. All development efforts will be focused on making the graphomate chartrix the best IBCS® charting visual there is. Video Link: graphomate chartrix for Microsoft Power BI AppSource Link: graphomate chartrix Sample Report Link Drill Down Bubble PRO by ZoomCharts Drill Down Bubble PRO is a Power BI visual designed for exploring relationships, trends, and outliers across multiple dimensions of data. It adds richer exploration, selection, and analytical capabilities directly inside the visual. Key features include: Multi-level drill down to explore data hierarchies from a high-level overview to detailed insights. Pan and zoom controls to navigate dense datasets and focus on specific clusters or individual data points. Area and lasso selection to quickly isolate groups of bubbles and use selections for interactive analysis and filtering. Dynamic regression lines that recalculate as the displayed data changes, making trends and relationships easier to identify. Line and area thresholds to highlight targets, ranges, exceptions, or other important business benchmarks. Area shading to visually group and compare selected segments of data. 200+ formatting settings to tailor the chart to different reporting and branding needs. Figure: Drill Down Bubble PRO demonstrates multi-level drill down, panning, and zoom controls for exploring data from high-level patterns to detailed points. These capabilities make Drill Down Bubble PRO especially useful for customer segmentation, sales analysis, portfolio analysis, performance monitoring, and other scenarios where users need to actively explore patterns rather than simply display them. Get on Markeplace Commenting in view mode: introducing Zebra BI Tables+ & Charts+ It's month-end. A regional manager opens the report, spots a variance in their region, and knows exactly why it happened. But the report isn't theirs to edit, so the explanation ends up where it always does: a screenshot pasted into PowerPoint, emailed around, detached from the number that prompted it. That's the collaboration gap. Your report shows what happened; the why and the what next leave the report and get lost. Meet Zebra BI Tables+ and Charts+: two new visuals that keep everything existing Zebra BI Tables and Charts offer and add a built-in collaboration layer. Report viewers can add comments directly on a data point, in view mode, with no Power BI edit access. Each comment is anchored to the exact figure and stored in your own SharePoint file. Zebra BI stores nothing. ting files from SharePoint, and collaborate directly in view mode. So instead of screenshotting insights into PowerPoint or maintaining a custom workaround, the whole team explains and decides right on the report. Instead of slides or emails, the next steps can be defined directly on the spot. Stop losing good decisions to a missing context. Start making them on the report. Try Zebra BI Tables+ and Charts+ free for 14 days on AppSource. Network Graph by Powerviz The Powerviz Network Graph is a visual representation of Nodes and the relationships or connections between them. Its primary purpose is to illustrate how different entities are related or interact with one another. Key Features Line Options: Customise node links with different styles and colors. Node Shape: Choose from various shapes, icons, or upload your own. Labels: Display categories, values, and percentage labels. Data Colors: Access 30+ color palettes, including color-blind-safe options. Fill Patterns: Highlight nodes with patterns or upload your own. Conditional Formatting: Highlight outliers based on measures or category rules. Clusters: Group related nodes to reveal patterns. Relationships: Analyze node connections at a glance. Animation: Add pop-ups and highlight effects. Import/Export: Save and reuse themes easily. Toolbars: Gain advanced control over the graph. Other features included are Sorting, Ranking, Lasso / Reverse Lasso, Grid View and more. Business Use Cases Customer Relationship Management (CRM), Supply Chain Optimization, Social Network Analysis (SNA). Resources Try Network Graph visual for FREE from AppSource Check out all features of the visual Step-by-step instructions YouTube Video Learn more about visuals Follow Powerviz on LinkedIn Hierarchical Bar Chart New, exciting changes were made to Hierarchical Bar Chart. Bubble Matrix for stacks - The visual now provides the option to show stacks as bubbles below the bars. lues into bar-and-bubble matrix layouts for clearer comparison of category totals and component contributions. Display Stacks as Clustered Columns - From the format pane settings, you can choose to display stacks as clustered column chart. Filter using legends - You can click on a stack legend to filter out other stacks. On mouse hover relevant stack gets highlighted. Stack ribbons and %age of total - You can now choose to connect stacks with ribbon and show percentage of total for each stack. Resources Check out the Hierarchical Bar Chart Update YouTube video. Download the visual from APPSOURCE Download a sample pbix file For more information refer to Hierarchical Bar Chart or contact us. That’s a wrap! The European Microsoft Fabric + SQL Community Conference is just getting started, and there's never been a more exciting time to be part of the Power BI community. We hope these updates help you discover new capabilities, streamline your workflows, and get even more value from your data. Be sure to explore the links throughout this post for deeper technical guidance and follow along with the latest announcements and sessions from Barcelona.
Find expensive queries from Capacity Metrics (Generally Available)
When warehouse capacity usage spikes, you need to quickly understand what ran, which warehouse drove the usage, and which queries require investigation. The Monitor in warehouse action in the Microsoft Fabric Capacity Metrics app connects the capacity-level view directly to Warehouse Monitor. It opens the selected warehouse with the relevant time window already applied, eliminating manual correlation across monitoring experiences. Follow the activity into your warehouse Open Capacity Metrics: From the Compute page, select your capacity and review CU % over time. Capacity Units, or CUs, represent the compute consumption tracked for the capacity. Choose a timepoint: Select the usage increase you want to investigate, and then select Explore and open TimePoint Detail. Choose an operation window: Under Background operations for time range, select a supported warehouse query operation whose Start and End times cover the interval. Then select Monitor in warehouse. Explore Warehouse Monitor: Open Query history to review statements that ran during the selected interval. Access required: Access to the Capacity Metrics app and the Admin role in the workspace containing the warehouse. For supported operations and navigation, refer to the Monitor in warehouse documentation. Find the queries worth investigating Start with CPU time. Add the column through Column options and sort from highest to lowest. CPU time is the processor time allocated to an execution. It is not elapsed duration or the Capacity Units billed for an individual query. No single metric explains the complete workload. Review these columns together: Data scanned: Identify statements that read large volumes of data. Compare OneLake reads with local disk, and memory reads to understand caching behavior. Result cache hit: A value of 2 means the query reused a cached result, 1 means the execution created a result set cache, and 0 means result caching did not apply. Query text: Review joins, predicates, and filters for unnecessary scans or processing. Label: Connect statements to a workload, business process, or test variation. Is distributed: Separate distributed executions, represented by 1, from nondistributed requests, represented by 0. For queries with high CPU time or data scanned, select View similar runs to determine whether the behavior is recurring or isolated. Add Query Insights fields such as application, SQL pool, status, and error code to identify the originating workload and distinguish expensive successful executions from failed or interrupted ones. For field definitions, refer to the query execution history column reference documentation. Make the same correlation with AI The Data Warehouse operations skill in Skills for Fabric can correlate Capacity Metrics data with Query Insights activity for the same warehouse and time window, using your existing permissions. Example prompt: Investigate the capacity spike for my warehouse from 14:00 to 15:00 UTC on November 3, 2026. Identify queries with high CPU time or data scanned, explain why each query stands out, and suggest the next investigation step. Review the supporting metrics and query details before making tuning or workload-management decisions. Next steps Try Monitor in warehouse the next time you see a capacity usage increase. Start with CPU time and data scanned, compare similar runs, and use workload metadata to determine what drove the activity. For more guidance, refer to the Warehouse performance guidelines, query blocking troubleshooting, and Monitor T-SQL queries documentation.Power BI reports support OAP exceptions for semantic models in separate workspaces (Preview)
Workspace outbound access protection (OAP) helps you control where data in a Microsoft Fabric workspace can flow. The initial preview for Power BI reports, launched in June, required a report in an OAP-protected workspace to use a semantic model in that same workspace. Customer feedback highlighted that this was too restrictive. With this improvement, a report can now query a semantic model in another workspace provided a workspace administrator explicitly allowed that destination through an OAP exception policy. Apply exception policies to allow report-to-model connections OAP continues to block outbound report-to-model connections by default. When a report opens, Power BI evaluates the report workspace policy before it renders the report in the browser. If the destination workspace is covered by an applicable exception, the report can connect to its semantic model. Otherwise, Power BI blocks the connection, and the report does not open. The report honors the policy that a workspace admin configured for the semantic model destination. You don't configure an exception on each report, and you don't need to move the report and semantic model into the same workspace. The OAP exception policy supports a common Power BI architecture: a central team manages shared semantic models in one workspace, while business teams build reports in separate workspaces. You can preserve that separation of ownership without removing the outbound boundary from the report workspace. See the improvement in action The following example shows a report stored in an OAP-protected workspace, and its semantic model is stored in another workspace. First, the report does not have an applicable exception policy. Power BI blocks the cross-workspace connection and displays the following error because the report can't access its semantic model. Next, a workspace admin creates an exception policy for the semantic model workspace. In the workspace settings under Outbound networking, select Add new cloud connection rule, select Power BI Semantic Model as the Connection Kind, and select the desired semantic model workspace under Workspace exception, as in the following screenshot. Select Add, and then select Save to save the Data Connection rules. After the policy takes effect, the same report loads and its visuals render successfully. The report binding doesn't change. The OAP policy determines whether the cross-workspace connection is allowed. The semantic model remains subject to its own OAP controls. Connections from the semantic model to cloud databases, on-premises systems through gateways, lakehouses, warehouses, and other sources are still evaluated against the semantic model workspace's data connection rules. Make sure you enable OAP for both, the report workspace as well as for the semantic model workspace. Next steps Work with your workspace admin to confirm that your report workspace meets the OAP prerequisites and that OAP is enabled. Then create an exception policy for each approved semantic model destination. Policy changes can take about 15 minutes to propagate. For configuration details, refer to the Workspace outbound access protection for Power BI reports documentation. To understand downstream enforcement, refer to Workspace outbound access protection for semantic models.
Build more connected workflows with Fabric Actions and Business Actions in Fabric Pipelines (Preview)
Modern data workflows rarely stop at moving and transforming data. Once data is ready, you may need to trigger another operation in Fabric, refresh a semantic model, update a business application, send a notification, generate a document, or kick off the next step in a business process. With Fabric Actions and Business Actions activities in Microsoft Fabric Data Factory, you can bring these steps directly into your Fabric pipelines. Together, these activities make it easier to orchestrate workflows across Fabric and the business applications your organization relies on, without having to build and maintain custom API integrations for every scenario. We’re continuing to expand what you can do with these activities, with support for more Fabric operations and 25 additional third-party connectors for Business Actions. Bring Fabric operations directly into your pipelines The Fabric Actions activity lets you invoke supported Fabric REST API operations directly from a pipeline. Instead of manually constructing REST API requests and managing the underlying authentication and request details, you can select the Fabric operation you need, configure its inputs, and incorporate it into the rest of your pipeline workflow. We’re expanding the range of supported Fabric actions across experiences such as Lakehouse, Warehouse, Notebook, Copy Job, Dataflow, Eventhouse, Eventstream, semantic models, OneLake shortcuts, Workspaces, Capacity, and more. This gives you more ways to automate Fabric as part of an end-to-end workflow. For example, you could run a Notebook as part of your data processing flow, manage a OneLake shortcut, perform a Lakehouse operation, or refresh a semantic model after new data is ready, all orchestrated from the same pipeline. Fabric Actions also provides built-in connection and credential handling, helping reduce the authentication and integration work that would otherwise be required when calling supported Fabric APIs directly. The following visual shows how you can select and configure a Fabric operation directly within your pipeline. Connect your pipelines to more business applications While Fabric Actions helps you orchestrate operations within Fabric, Business Actions helps connect your data workflows to the business applications and services where business processes happen. With this release, we’re expanding Business Actions with 25 additional third-party connectors, opening new possibilities across CRM, communications, document generation and signing, security, financial planning, project management, marketing, and more. For example, you can use Business Actions to: Send SMS notifications with D7SMS. Generate contracts, invoices, proposals, and other documents with Formstack Documents. Automate CRM and sales processes with connectors such as Pipeliner CRM and Commercient. Incorporate electronic signature workflows with Nitro Sign Enterprise Verified. Connect pipeline workflows with project and portfolio management systems. Integrate security and threat intelligence operations with services such as RiskIQ. Automate website content publishing with WP Connectr for WordPress. These additions build on the Business Actions experience to give pipeline authors more ways to connect data with the systems and processes that teams use every day. The following visual highlights some of the business applications that can be connected to your pipeline using Business Actions. Find and configure the action you need As we expand the actions available to pipeline authors, we’re also making them easier to discover and configure. Discover Fabric operations With the updated Fabric Actions experience, you can browse or search for supported Fabric operations instead of needing to know the underlying REST API endpoint ahead of time. Once you select an operation, the activity surfaces the relevant configuration and required parameters. You can then select an existing Fabric connection or create one, provide the required inputs, and use dynamic content where supported. The following visual shows the updated experience for discovering the Fabric operation you want to use. Configure your action Getting started is straightforward. Add Fabric Actions or Business Actions to your pipeline, find the operation you want to perform, configure the required inputs and connection, and incorporate the activity into your pipeline flow. For Fabric Actions: Create or open a pipeline in Microsoft Fabric Data Factory. Add the Fabric Actions activity to the pipeline. Browse or search for the Fabric operation you want to perform. Select or create a Fabric connection. Configure the required inputs. Save and run your pipeline. When the activity runs, the selected Fabric operation executes as part of the pipeline, with its response available through the activity output. Business Actions follows the same principle by providing structured configuration for supported business application operations, so you can incorporate business processes without starting from a custom API integration. Go from data workflows to business workflows The real power comes from combining Fabric Actions and Business Actions with the rest of your pipeline. Consider a pipeline that processes the latest sales data. Once processing completes, the same pipeline could refresh the semantic model used for reporting, create or update a record in a CRM system, generate a customer document, and send a notification that the latest information is ready. Or imagine a document workflow where a pipeline processes business data, generates a contract from that data, starts an electronic signature process, and continues downstream processing once the appropriate business step has taken place. Rather than building separate integrations for each part of the process, you can bring data processing, Fabric operations, and business actions together as part of a larger orchestrated workflow. This allows your pipelines to coordinate not only what happens to your data, but what happens next because of your data. The following visual shows an example of an end-to-end pipeline that brings data processing, Fabric operations, and business processes together. More actions, more possibilities We’re continuing to expand both Fabric Actions and Business Actions to give pipeline authors more ways to connect their data workflows with the next step in their business process. For Fabric Actions, that means broader coverage across Fabric workloads and platform operations, from Lakehouse, Warehouse, Notebook, and Copy Job to semantic models, OneLake shortcuts, Workspaces, Capacity, and more. For Business Actions, that means expanding the connector ecosystem so pipelines can interact with more of the applications and services organizations use every day. Our goal is to make these integrations easier to discover, configure, and incorporate into the pipelines you already build, so you can spend less time building integration plumbing and more time building end-to-end workflows. Get started To get started, open a pipeline in Microsoft Fabric Data Factory and explore the Fabric Actions and Business Actions activities. Whether you’re automating an operation within Fabric, connecting your pipeline to a downstream business application, or building a workflow that spans both, Fabric Actions and Business Actions give you more ways to turn data into action directly from Fabric Pipelines. We’re excited to continue expanding the actions you can connect and automate as part of your Fabric data workflows. To learn more, check out the Use the Fabric actions activity in a pipeline and Use the business action activity in a pipeline documentation.Regular expression functions in Microsoft Fabric Data Warehouse (Preview)
Data warehouses routinely ingest valuable information embedded in free text, where inconsistent structure makes it difficult to query, connect, and analyze. Incoming values can also require quality checks before they reach curated tables. Microsoft Fabric Data Warehouse and the SQL analytics endpoint now support scalar regular expression functions in preview, so you can extract useful values, validate formats, standardize text, and mask sensitive data directly in T-SQL instead of adding a separate processing step. What’s new in preview Regular expressions provide a concise way to recognize, extract, and transform complex text patterns that would otherwise require multiple string operations. The preview introduces the following scalar functions: REGEXP_LIKE: checks whether text matches a pattern. REGEXP_REPLACE: replaces matching text to clean, standardize, or mask values. REGEXP_SUBSTR: extracts a substring that matches a pattern. REGEXP_INSTR: returns the position of a matching substring. REGEXP_COUNT: counts pattern occurrences in a string. Use these functions during refinement to turn identifiers embedded in free text into structured values and to flag malformed records before they reach downstream systems. The following scenarios demonstrate both uses. Extract useful values from raw text In this fictional example, inbound customer emails land in bronze.EmailMessages. The Sender column contains a value such as “Avery Smith”, and an order reference such as “ORD-10293” may appear in the Subject column. REGEXP_SUBSTR extracts the sender’s name, email address, company identifier, and order number as structured values that can be related to curated customer, company, and order data. For “Avery Smith ”, the query returns “Avery Smith” as the Name, “[email protected]” as the Email, and “contoso” as the Company. It also extracts the order number from the Subject column. Validate contact data before it reaches downstream systems Contact data in the silver.DimCustomer table can contain missing characters, extra spaces, or email addresses that do not follow the expected format. REGEXP_LIKE identifies records that fail the format check, so you can review, correct, or quarantine them before the dimension feeds reports, campaigns, and downstream applications. SELECT SourceCustomerId, EmailAddress FROM silver.DimCustomer WHERE NOT REGEXP_LIKE(EmailAddress, '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$'); The query isolates email addresses that do not match the expected format so they can be reviewed, corrected, or quarantined before the customer dimension is released to downstream consumers. Conclusion Regular expression functions help turn hard-to-use text into structured, trustworthy warehouse data. You can extract sender, company, and order details from inbound emails and validate contact values during refinement, all with concise T-SQL close to the source. The result is information that is easier to connect, analyze, and trust. Explore the preview and learn how to use regular expression functions in Fabric Data Warehouse in the documentation. Share your scenarios and feedback with the Microsoft Fabric community on Reddit.
Govern Fabric connections with admin APIs and data connection policies (Preview)
Co-author: Abhishek Narain Protect continuity, understand connection risk, and set tenant-wide guardrails Imagine that the person who built a business-critical pipeline has left your organization. The connection still exists, but nobody is sure who can manage it or whether its credentials will keep working. What begins as a handover problem quickly becomes a governance question: who owns your connections, where do they lead, and which identities should be allowed to use them? Microsoft Fabric brings these questions together through two complementary capabilities: Admin connection APIs give tenant administrators visibility and ownership-management tools across connection types. Data connection policies set preventive controls for cloud connections. Together, they support a practical sequence: restore responsibility, understand your connections, then enforce the authentication boundaries your organization needs. From recovery to prevention Keep work moving when a connection owner leaves A departure should not leave a connection without someone who can maintain it. When an existing connection has a single owner, a Fabric tenant administrator can use the admin connection APIs to grant the Owner role to a responsible successor, another administrator, or an appropriate service principal. This restores the ability to manage the connection and establishes clear accountability during the handover. Use the admin connection APIs to review current access, assign a responsible successor as an Owner, update an existing assignment, and remove access that is no longer appropriate. The role-assignment endpoints support GET, POST, PATCH, and DELETE operations; refer to Admin Connections REST API reference for endpoint syntax and examples. Ownership is only part of continuity. Granting Owner does not transfer or renew OAuth credentials, confer permissions on the source system, or guarantee that dependent workloads will run. The incoming owner must check the connection requirements, update or reauthenticate credentials where needed, and validate the workloads that depend on it. Treat that validation as part of offboarding, not a task to postpone until something fails. See your connections, endpoints, and access clearly A tenant-wide inventory helps administrators find ownership gaps, unexpected access, and connections that may require review before they become operational issues. The admin APIs provide visibility across all connection types, including connections you do not own or have permission to manage. By comparison, the standard Manage connections and gateways experience does not provide a tenant-wide inventory, even for administrators. Use the tenant-wide connections endpoint to collect the complete inventory, including all paginated results. The response includes connection names and IDs, connectivity and connector types, endpoint paths, privacy levels, and credential or authentication-type metadata—but not secret values. Combine this information with current role assignments to identify unexpected access and endpoints or domains that require closer review. Recency data can help prioritize the review. Created, last-linked, and last-credentials-used timestamps answer different questions: last linked indicates when the connection configuration was most recently associated with a workload, while last credentials used provides a runtime signal. These timestamps do not provide a complete historical audit log, an automatic dependency map, or proof that an apparently idle connection is safe to delete. Confirm critical dependencies with workload owners before making changes. This read-only demonstration uses a Python client to list tenant connections and inspect a connection role assignment. It does not change ownership. For the admin API endpoints and an example response, refer to List Connections (Admin) and List Connection Role Assignments (Admin). Try a read-only connection inventory app For a hands-on inventory, refer to the Fabric Connection Inventory sample app. It uses the admin connection APIs to list tenant connections and their Owner and PendingOwner assignments, with search and filters for reviewing connector types, endpoints, and ownership results. It does not change connections, assign owners, or enforce policies. This is a single-tenant deployment template, not a hosted app that readers can sign into. To use it, an organization must deploy its own instance in a workspace that supports Fabric Apps (Preview), configure a single-tenant Microsoft Entra app, grant delegated Tenant.Read.All consent, and sign in with a Fabric administrator account. See the repository’s setup instructions. Illustrative API examples To inventory connections across the tenant, an administrator can make a read-only request: GET https://api.fabric.microsoft.com/v1/admin/connections Authorization: Bearer <access-token> { "value": [ { "id": "11111111-1111-4111-8111-111111111111", "displayName": "ContosoConnection", "connectivityType": "ShareableCloud", "connectionDetails": { "type": "Web", "path": "https://www.contoso.com/" } } ] } If the response includes a continuationToken, use it to request the next page. For an ownership handoff, the following illustrative write request shows the payload for adding a user as an Owner. It was not part of the read-only GIF or the production test: POST https://api.fabric.microsoft.com/v1/admin/connections/11111111-1111-4111-8111-111111111111/roleAssignments Authorization: Bearer <access-token> Content-Type: application/json { "principal": { "id": "22222222-2222-4222-8222-222222222222", "type": "User" }, "role": "Owner" } An ownership assignment may require the incoming owner to reauthenticate. It does not transfer credentials or guarantee that dependent workloads will run. Make approved authentication methods the rule An inventory shows how connections authenticate today. An authentication allowlist turns your organization’s requirements into a tenant-wide boundary for cloud connections. Instead of relying on every creator to make the same choice, you define the methods that policy permits. An authentication allowlist helps administrators reduce inconsistent or noncompliant authentication choices across cloud connections. In the Fabric admin portal, select Data Policies in the left navigation, then open the Authentication allowlist tab. Add the approved authentication methods, turn on Restrict to allowlist, and select Save. Review the tenant-wide confirmation before committing. Select methods that meet your organization’s requirements and are supported by the relevant connectors; no single method is universally available or appropriate. When enforcement is enabled, methods outside the allowlist fail policy evaluation for existing as well as new cloud connections. Enable this carefully, because it can disrupt existing workflows. That makes the inventory essential preparation: identify affected connections, agree on supported alternatives with their owners, and plan credential changes before enabling the restriction. These controls govern cloud connections; they are not a promise of coverage for every gateway, desktop client, or data path. Define which Microsoft Entra tenants can authenticate connections An approved authentication method does not make every Microsoft Entra tenant acceptable. Organizations may also need to block connection authentication associated with unapproved tenants. The Tenant allowlist addresses this requirement by defining which Microsoft Entra tenants can be used for Entra-authenticated cloud connections, helping reduce the risk of authentication through unapproved tenant identities. On Tenant allowlist, select Add tenant ID and enter the approved tenant GUIDs. Validate each ID carefully: the experience does not look up friendly names, and the list supports up to 100 IDs. Turn on Restrict to allowlist, select Save, and review the tenant-wide confirmation. Once enforced, the restriction affects both existing and new Entra-authenticated cloud connections. Keep identity and destination controls distinct. The Authentication allowlist limits which methods cloud connections can use, while the Tenant allowlist limits which Microsoft Entra tenants they can authenticate with. Neither control approves destination endpoints nor acts as a firewall rule. Start with visibility, then enforce Before enabling enforcement, inventory your cloud connections, identify critical workloads and their owners, and confirm the authentication methods and Microsoft Entra tenant IDs they need. Review the Authentication allowlist and Tenant allowlist tabs together, then enable only the controls you intend to enforce. Each allowlist has its own Restrict to allowlist switch. Communicate the change and assess its effect on existing as well as new cloud connections; enforcement applies tenant-wide. Policy changes can take up to one hour to take effect. After enforcement begins, test affected cloud connections and dependent workloads. A noncompliant new connection is rejected; an existing connection may show Policy Evaluation Failure and go Offline. Open the connection details to identify the cause, then work with the connection owner and tenant admin to resolve the authentication-method or tenant-policy mismatch. Ownership transfer alone does not resolve a policy failure. Closing Start with a complete inventory and an ownership review of critical connections. Use that evidence to define and validate authentication-method and Microsoft Entra tenant allowlists. These capabilities cannot prevent every outage or misuse, but they can reduce unmanaged handovers, clarify decisions about access and endpoints, and apply preventive controls that reflect your organization’s requirements. To plan your implementation, review the guidance for data source management and data connection policies.Build, deploy, and govern Microsoft Fabric at scale
If you haven’t already, check out Arun Ulag’s hero blog “FabCon and SQLCon 2026 in Barcelona: Building the data foundation for Microsoft Copilot and Agents” for a complete look at all of our FabCon and SQLCon announcements across both Fabric and our database offerings. Getting a data project working is only the beginning. As AI makes it easier for more people to build applications, explore information, and create agents, the harder questions arrive sooner: can the solution be deployed consistently, can a team explain what changed, and will someone notice when a dependency fails? Developers need room to experiment, but they also need a dependable route from an isolated feature branch to a production workload that others can operate. Manual setup, disconnected monitoring, and unclear data context make that route harder to repeat. Administrators face the other side of that growth. More workspaces, users, and workloads mean more decisions about access, compute, spending, and accountability. A capacity spike can affect an unrelated team; a broad security setting may not fit every project. Admins need controls that reflect organizational requirements without turning each development step into a permission request. Developers, in turn, need those boundaries to be understandable and built into their workflows, rather than discovered just before release. Today, we're announcing Microsoft Fabric platform updates to help you tackle both sides of that challenge. They connect operational signals with investigation, make delivery more repeatable, and bring governed discovery into the tools you use. We're also expanding your options for managing compute demand and applying controls across your estate. Introducing observability in Fabric (Preview) A failed job rarely tells the whole story. With the introduction of observability in Fabric, you can connect signals across jobs, workspaces, items, and capacities rather than investigate each in isolation. A Monitor item acts as a single management unit across capacities and your tenant, bringing early detection, contextual investigation, and central management into one operational experience. Unified workspace monitoring (Preview) We're introducing unified workspace monitoring so you can choose which Eventhouse receives your telemetry and consolidate multiple workspaces into that shared store. Instead of monitoring workspaces individually, you can bring related signals together and manage their storage centrally. You control retention and caching policies to suit your investigation and operational needs. When a failure crosses workspace boundaries, for example, you can correlate the telemetry in one place and follow the issue across those boundaries. Most Fabric items will be available at launch, with additional workloads becoming available over time. The new experience also simplifies how you connect monitoring to your own tools. A custom endpoint on the monitoring Event Stream lets you copy data to external or custom destinations, while public APIs support integration with your external observability tools. Simplified, API-backed onboarding makes setup repeatable for automation and agents. You can establish a shared monitoring approach, then extend it to additional workspaces without treating every setup as a separate manual exercise. Refreshed Monitor Hub (Preview) The refreshed Monitor Hub helps you see where attention is needed before opening individual investigations. We're adding ready-made, at-scale views across workloads, jobs, apps, agents, alerts, and capacities, with a centralized health overview and data health monitoring. That broader view helps you spot emerging issues and consider their downstream impact rather than starting with a single failed activity. Capacity consumption and available headroom sit alongside operational signals, so you can consider resource pressure as you assess an issue. Start with the health overview, narrow your focus to the affected area, and move into investigation with that context. The hub connects navigation and operational visibility; the capacity administration actions described later let you respond when the next step is a control change. Agentic investigation and alerting with operations agents and Activator We're also adding the ability to use operations agents to investigate end-to-end causes, develop evidence-backed hypotheses, assess impact, and recommend next steps. You can engage with the investigation, refine its direction, and choose your response. This brings the supporting evidence and relevant dependencies into the conversation instead of leaving you to assemble every clue yourself. Currently this capability can help you investigate pipeline failures, with further support planned. New Activator-powered job alerts notify you about successes as well as failures. You can automate alerts and configure responses, connecting investigation with the operational workflows your team uses. Together, these enhancements help you move from noticing an event to understanding its likely impact and deciding what to do next. Repeatable delivery and governed discovery for developers Operational confidence starts before deployment. The latest enhancements, designed with developers in mind, help you package a solution, review changes, move definitions between environments, and find reusable data worth reusing with fewer manual handoffs between those steps. Introducing deployment plans (Preview) With the deployment plans now in preview as first-class workspace items, you can define the exact deployment order on a visual canvas, with YAML as the source of truth. You can include pre- and post-deployment steps, such as hydrating a lakehouse with a notebook, running a pipeline before dependent items, or validating data after deployment. Your plan follows the solution through Git branch-out, initial sync, updates, deployment pipelines, and bulk import. Preparation and validation become part of the deployment sequence rather than a separate checklist. Bulk Item Definition APIs, quotas, and API limits (Generally Available and Preview) Bulk import and export item definition APIs are also now generally available. You can move multiple definitions in one call; imports automatically determine deployment order and update references for the destination workspace. This supports workspace-as-code, CI/CD, and migration. We're also enhancing the Fabric API platform with a unified quota model and increased limits for core APIs. These updates provide more consistent throttling and quota management while supporting higher-scale automation, CI/CD, and enterprise workloads, making it easier to build and operate Fabric solutions at scale. Git integration enhancements (Generally Available and Preview) The new branch workspace administration delegation capability, now in preview, gives developers a governed, self-service way to create branch workspaces without permission to create workspaces or assign capacity. Administrators define the branch workspace admin profile, including the role, admins, capacity, and delegated settings applied to each new branch workspace, helping teams move faster while maintaining consistent guardrails. We're also expanding the Git workflow with file-level commits for supported items (Preview) and contributor branch switching (Preview). You can commit only the files that are ready while leaving unfinished changes in the workspace, and contributors can switch the Git branch connected to a workspace when administrators enable the capability. Additionally, selective branching, change comparison and commits, and branched workspace relationships, now generally available, helping teams keep feature work focused, review changes before acting, and manage branching from a clearer source control experience. Discover data in OneLake catalog and your coding workflow The OneLake catalog gives you a richer, more granular way to explore and understand data across Fabric before you use it. With the latest updates, you can go beyond finding Fabric items to explore individual tables and columns, review descriptions, and preview the underlying data directly in the catalog. Quick actions, personalized views, and filters, including domains and tags, add business context so you can evaluate whether data is right for your needs before you start working with it (Generally Available). We've also expanded the OneLake catalog search API to return relevance-ranked Fabric items, OneLake tables from lakehouses, mirrored sources, and semantic model tables in one result set (Preview). This brings the same granular discovery to programmatic search, helping applications find relevant data across Fabric regardless of where it lives. OneLake catalog discovery in GitHub Copilot CLI is now generally available through Skills for Fabric. You can find Fabric items and tables from the CLI before writing code, bringing this richer, governed discovery experience directly into your coding workflow rather than requiring a separate search. Bring catalog discovery into Excel and Microsoft Foundry Finally, OneLake catalog in Excel is now in preview, enabling you to discover and analyze Fabric data in your workbooks without copying or moving the underlying source data. OneLake row- and column-level security and Microsoft Purview label-based protections apply, connecting familiar analysis with the protections associated with your source. New OneLake catalog additions in Microsoft Foundry bring enterprise data discovery into your AI development workflow (Preview). With an embedded catalog and a unified view across Fabric and Foundry, you can find trusted data and add it to knowledge, agents, and workflows. Effectively administer capacities and spending As your solutions reach production, capacity administrators need to optimize spend for steady demand while seamlessly managing bursts. With today’s announcements, we are adding new billing choices and capacity controls, as well as tools that help you investigate usage, automate responses, and act across capacities. Introducing on-demand compute and zero-provisioned capacity (Preview) As data and AI workloads grow, organizations need flexible ways to align costs with actual usage. Building on Autoscale Billing for Spark, we're introducing on-demand billing across Microsoft Fabric in preview soon, enabling workloads to scale elastically when needed, minimizing throttling during demand spikes, and allowing you to pay only for the compute you consume. We're also introducing Fabric zero-provisioned (F0), a new entry point to Fabric and OneLake that removes the need to provision compute before getting started. With on-demand billing enabled by default, organizations can immediately access Fabric services and pay only for the resources they use. Together, on-demand billing and Fabric zero-provisioned make it easier to start small, scale as demand grows, and combine consumption-based pricing with reserved or provisioned capacity to optimize both performance and cost. These capabilities will be available in the coming weeks. Whether you're running workloads that tend to spike, experimenting with new projects, or supporting production applications, on-demand billing gives you greater flexibility without requiring upfront capacity planning. Surge protection, overage, and larger capacities (Generally Available) Workspace-level surge protection will be generally available soon. You can set a workspace consumption limit, automatically isolating runaway or non-critical workloads so they don't impact mission-critical workloads or cause capacity-wide throttling. You can manage these controls in OneLake catalog or Monitor Hub, which also allows you to mark mission-critical workspaces exempt from the limit. Additionally, capacity overage is now generally available, letting you use additional paid compute with configured spending thresholds and notifications rather than sizing capacity solely for rare peaks. For sustained high demand, we've added the F4096 and F8192 capacity SKUs (also Generally Available), extending your options for larger workloads. Monitor, act, and automate your capacities Monitoring helps you understand who's consuming resources, identify demand spikes, and ensure critical workloads continue to perform as expected. New capacity metrics app enhancements help you investigate health-state duration, capacity units per second, daily and hourly heatmaps, and top item contributors (Generally Available). Clearer drilldowns support deeper analysis, while chargeback app integration helps you allocate usage. Capacity overview events in Real-Time Hub (Generally Available), with new operation events (Preview) adding workspace- and item-level visibility. These signals enable proactive capacity monitoring by helping administrators identify emerging hotspots, usage anomalies, and resource-intensive operations before they impact users. Connect them to Real-Time Intelligence, Eventhouse, and Activator to automate alerts and actions, retain history for capacity planning, or integrate insights into your existing monitoring systems. With the refreshed Monitor Hub, we're taking the first step toward bringing capacity insights and management actions together in a single experience. Capacity Insights & Actions (preview) lets administrators identify emerging issues and immediately respond by adjusting surge and overage settings, migrating workspaces, or resizing capacity. Use Monitor Hub for monitoring and operational decisions, and the capacity metrics app for deeper usage analysis. Unify governance, security, and control in the OneLake catalog As AI helps more people build with data, tenant admins are responsible for governing an estate that’s growing in both size and complexity. More workspaces, data items, and access requests mean more decisions about what people can share, which settings they can change, and how to protect sensitive data. Admins need to support new projects without turning every decision into a manual review, or losing visibility into how data is used. That balance between enabling teams and maintaining the right guardrails is critical. As Jayakumar Pankajatchan, Distinguished Engineer at KPMG, shared, “Client trust starts with security. Every engagement needs clear data boundaries and strong guardrails, so information flows only where intended. With Microsoft Fabric, we strengthen governance across engagements while enabling teams to deliver insights with confidence at scale.” We’re expanding governance and security in Fabric to help organizations put those guardrails into practice without slowing teams down. With more centralized management, AI-assisted governance guidance, granular policies, and broader network protection, you can give your teams room to innovate while maintaining controls that reflect your organization’s requirements. Introducing policies in Fabric (Preview) With policies in Fabric (Preview), we're introducing precise, attribute-based controls that help organizations enforce governance requirements based on user and data attributes, rather than relying solely on broad settings. Policies enable granular controls for key scenarios, with item creation and workspace security supported at launch and external data sharing coming soon. A centralized policy management experience, monitoring, APIs, and CI/CD integration support policy lifecycle management at scale, supporting more consistent and automated governance across your organization. Figure: Creating an item creation policy with attribute-based conditions and controls. "Fabric’s Item Creation Policies have strengthened our governance controls for Microsoft Fabric, allowing us to scale innovation across the organization by empowering users with the right capabilities while maintaining clear boundaries for platform management and compliance,” said Bernard Beeftink Lead Product Owner, BI, ABN AMRO. Centralizing governance in the OneLake catalog We're expanding the OneLake catalog Govern experience (Generally Available) with centralized governance capabilities that bring management of tenants, domains, capacities, workspaces, tags, and policies into a unified experience. Rich contextual signals, insights, and recommendations help administrators better understand their governance posture and take informed action across their data estate. We're also introducing Govern Skills as part of skills-for-fabric. Govern Skills provide AI-powered guidance across the health, security, and trustworthiness of your data. Govern Skills help administrators identify governance risks, monitor the health of their data estate, and take recommended actions to maintain a secure, trusted, and well-governed foundation for analytics and AI. Outbound access protection expansion (Generally Available and Preview) We've expanded outbound access protection to OneLake shortcuts (Generally Available), along with new coverage for maps in Fabric and operations agents (Preview). You can extend your outbound controls across these experiences while building on existing foundations such as Microsoft Entra, Private Link, customer-managed keys, and workspace IP firewall rules. FQDN allowlist for outbound protected workspaces (Preview) FQDN support for Spark simplifies secure connectivity for organizations using OAP-enforced Fabric workspaces, where Private Endpoints are often required to access dependent services. Instead of creating and managing Private Endpoints for every resource a Spark workload needs to reach, administrators can use domain-based network controls to securely enable connectivity through approved FQDNs. This reduces networking complexity, lowers operational overhead, and accelerates onboarding while maintaining enterprise security and compliance requirements. This capability will be available in the coming weeks. Fabric availability in Microsoft 365 Government Community Cloud High (GCC High) We are also expanding Microsoft Fabric to Microsoft 365 Government Community Cloud High (GCC High) customers. Support for GCC High extends Fabric to organizations that require U.S. sovereign cloud environments and compliance with frameworks such as DoD Impact Level 4, CJIS, DFARS, and NIST 800-171. Put the updates to work Start with the friction you encounter most: investigating failures, reproducing deployments, finding data, or managing demand and controls. Our updates connect those responsibilities without requiring every team to use the same workflow. Match adoption to your readiness requirements, then extend your approach as your data estate grows. In addition to the announcements above, we are also rolling out a broad set of innovation across Fabric. For a broad overview of all these announcements, read Arun Ulag’s hero blog “FabCon and SQLCon 2026 in Barcelona: Building the data foundation for Microsoft Copilot and Agents.” If you want a more detailed look, visit the Fabric September 2026 feature summary blog, the Power BI September 2026 feature summary blog, and the latest posts on the Fabric Updates channel and the Azure Data Tech Community blog channel.
More ways to use scalar UDFs in Microsoft Fabric Data Warehouse (Preview)
Scalar user-defined functions (UDFs) let data teams define a business rule once and reuse it across workloads in both Warehouse and the SQL analytics endpoint in Microsoft Fabric. This helps teams maintain consistent logic without duplicating it across queries. Some business rules require more than a single expression. They use procedural logic such as conditional branches, multiple RETURN statements, or WHILE loops. Expression Block inlining compiles and executes this logic in a distributed manner, helping reusable functions scale across analytical workloads. Building on that foundation, this update brings several improvements: More natural loop control and broader query-shape support. Automatic adoption of newly supported capabilities by existing functions, without recreating or altering them. Inlineability validation for new or changed functions, with diagnostics that explain any gaps and an explicit WITH INLINE = AUTO override when a non-inlineable function is acceptable. Express loop intent with BREAK and CONTINUE Loops often need to skip the rest of the current iteration or stop processing entirely. Without CONTINUE and BREAK, developers typically rely on extra flags, nested IF blocks, or repeated conditions. Those workarounds make the control flow harder to read and more difficult to update safely. Consider a function that standardizes tracking codes received from carrier and warehouse systems. Formatting characters such as spaces, hyphens, and slashes should be ignored. A pipe character marks the beginning of an operational note, so the function should stop there. CREATE OR ALTER FUNCTION dbo.fn_NormalizeTrackingCode (@Input VARCHAR(MAX)) RETURNS VARCHAR(MAX) AS BEGIN IF @Input IS NULL RETURN NULL; DECLARE @Result VARCHAR(MAX) = ''; DECLARE @Character VARCHAR(4); DECLARE @Position INT = 1; WHILE @Position <= LEN(@Input) BEGIN SET @Character = SUBSTRING(@Input, @Position, 1); SET @Position = @Position + 1; IF @Character = '|' BREAK; IF @Character = ' ' OR @Character = '-' OR @Character = '/' CONTINUE; SET @Result = @Result + UPPER(@Character); END; RETURN @Result; END; In this example, CONTINUE skips formatting characters, while BREAK stops processing when the operational note begins. The function therefore follows the business rule without a separate stop flag or another level of nesting. For an input such as "northwind-1000 / 1234 | imported from partner API", the function returns "NORTHWIND10001234". Use large-value data types in more query shapes The example uses VARCHAR(MAX) for both the parameter and the return type. Previously, MAX data types relied on Scalar UDF inlining and were subject to its calling-query restrictions. Expression Block inlining now supports VARCHAR(MAX), NVARCHAR(MAX), and VARBINARY(MAX) parameters, local variables, and return values. The function can keep its MAX types and be called from various query shapes. The following CTE is one example: it standardizes each event, then summarizes the number of source formats and standardized codes for each carrier. WITH StandardizedEvents AS ( SELECT ShipmentId, CarrierCode, RawTrackingCode, dbo.fn_NormalizeTrackingCode(RawTrackingCode) AS StandardizedCode FROM dbo.TrackingEvents WHERE RawTrackingCode IS NOT NULL ) SELECT CarrierCode, COUNT_BIG(*) AS EventCount, COUNT(DISTINCT RawTrackingCode) AS RawCodeCount, COUNT(DISTINCT StandardizedCode) AS StandardizedCodeCount FROM StandardizedEvents GROUP BY CarrierCode ORDER BY CarrierCode; You no longer need to choose between retaining MAX parameters and return types and using the query structure that best expresses your intent. Call scalar UDFs in IF EXISTS queries Procedural batches frequently need to ask whether any row meets a reusable business rule before taking the next action. The query inside IF EXISTS can now call a scalar UDF that uses Expression Block inlining. The following statement checks whether the tracking event table contains a specific standardized code. The function owns the normalization rule, while the batch owns the decision about what to do when a matching row exists. IF EXISTS ( SELECT 1 FROM dbo.TrackingEvents WHERE dbo.fn_NormalizeTrackingCode(RawTrackingCode) = 'NORTHWIND10001234' ) BEGIN SELECT 'Matching shipment found' AS ValidationResult; END ELSE BEGIN SELECT 'No matching shipment found' AS ValidationResult; END; This pattern keeps the existence check set-based and keeps the reusable scalar logic in one function. It is useful for validation gates, conditional batch steps, data-quality checks, and orchestration procedures that need to branch on the presence of qualifying rows. Existing functions gain new capabilities automatically As inlining support expands, your existing UDFs can become inlineable, run more efficiently, or become available in additional query shapes without being recreated or altered. The function text remains the same, while its current inlineability is reflected in the sys.sql_modules catalog view. SELECT SCHEMA_NAME(o.schema_id) AS FunctionSchema, o.name AS FunctionName, m.is_inlineable AS IsInlineable, m.inline_eligibility_mask AS InlineEligibilityMask FROM sys.objects AS o INNER JOIN sys.sql_modules AS m ON o.object_id = m.object_id WHERE o.type = 'FN'; The is_inlineable value indicates whether the function can be inlined, and inline_eligibility_mask identifies the applicable inlining technique. Check these values to confirm current service behavior because a function’s eligibility can change as inlining support expands. Default inlineability checks with an explicit override CREATE OR ALTER FUNCTION now checks inlineability by default. When a definition does not meet the inlining requirements, the statement is rejected, and the error identifies what prevents inlining. This catches compatibility gaps when the function is defined, before it can be referenced by a query. When a non-inlineable function is acceptable given its business context, WITH INLINE = AUTO explicitly overrides the default creation requirement. For example, the following function reads a table and uses multiple RETURN statements. It can still be useful as a standalone existence check even though it is not inlineable. CREATE OR ALTER FUNCTION dbo.fn_HasTrackingEvents (@CarrierCode VARCHAR(20)) RETURNS BIT WITH INLINE = AUTO AS BEGIN IF EXISTS ( SELECT 1 FROM dbo.TrackingEvents WHERE CarrierCode = @CarrierCode ) RETURN 1; RETURN 0; END; WITH INLINE = AUTO does not make a function inlineable or change the execution behavior of a function that is already inlineable. It explicitly allows creation of an intentionally non-inlineable standalone function. What's next Existing functions gain these capabilities automatically. First, check their status in the system catalog, then test the new query shapes with your procedural scalar UDFs. For the current syntax, metadata, and inlining requirements, refer to CREATE FUNCTION for Fabric Data Warehouse. For a guided introduction, refer to Create scalar user-defined functions in Microsoft Fabric Data Warehouse. To share a specific scenario or feedback, email Fabric DW functions feedback.
