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.
Manage semantic model settings in context with the default settings pane (Preview)
The semantic model settings pane is becoming the default way to configure semantic models in the Power BI service. The pane opens alongside your workspace, so you can review and change settings without leaving the current page. It provides the same settings as the full semantic model settings page while keeping the surrounding context visible. The classic settings page remains available during this transition, but it no longer opens first. This change builds on the settings pane preview and provides a more focused experience for managing semantic models. Why it matters The pane helps you stay in context while you manage a semantic model. It opens on the right side of the browser window and keeps your workspace visible. Settings are organized into expandable sections and tabs, including refresh, data access, performance, and OneDrive and SharePoint. You can use the search box at the top of the pane to find a setting across all sections and tabs. For example, enter "re" and select View refresh history to go directly to refresh history instead of opening sections one at a time. This organization is especially useful for semantic models with several connection, refresh, or performance settings. You can review a setting, make a change, and return to your work without navigating to a separate page. What's changing The settings pane was an optional experience earlier in the preview. As this change rolls out, the pane opens by default when you open settings for a semantic model. The rollout is gradual, so the timing can vary by environment. The pane includes the settings available on the full settings page. Its main area groups related settings into expandable sections, and the tabs at the top organize settings by category. Use the search box when you know the setting you want or browse the sections to review related options together. If you prefer the full-page experience, select Open settings page at the bottom of the pane. The classic page opens in the same browser window. This option can help when you want to compare settings across semantic models or continue using a familiar workflow during the transition. The classic settings page will be retired over time, so the switchback option is intended to support the transition. We're also working to consolidate related settings, including scheduled refresh and data connections. These planned improvements apply to the settings pane. The preview experience and behavior might change before general availability. Next steps Understand Semantic model permissions in Power BI. Learn how to use the pane in Manage semantic model settings in the settings pane. Open the settings for one of your semantic models and explore the grouped sections and search. Share feature suggestions through Fabric Community Ideas. Share feedback about the preview in the comments.Modern Power BI architecture choices for reporting on Azure Databricks: A performance benchmark for Power BI storage modes
Many enterprise Power BI semantic models use Azure Databricks as a data source. When building these models, developers and architects face an early and consequential decision: which storage mode to use. Cost, security, and ease of development and tuning all factor in — but report performance is probably the most important of them, because reports that are slow to load are one of the most common causes of end-user dissatisfaction. In practice, that decision is often made on intuition rather than evidence. To help change that, we've published a new white paper, Modern Power BI Architecture Choices for Reporting on Azure Databricks, benchmarking four ways of serving the same Delta tables to a Power BI report: Direct Lake on OneLake — over Delta tables in a Fabric lakehouse or warehouse Direct Lake on mirrored Unity Catalog tables — shortcuts, no copy DirectQuery — on a Databricks SQL warehouse Composite Model on Databricks — DirectQuery combined with Import-mode aggregations Figure: The four Power BI storage modes benchmarked to evaluate their impact on report performance and scalability. What the results suggest: there's no universal winner — but there are clear patterns. Direct Lake on OneLake performed well across the widest range of situations in this benchmark. It's highly competitive at smaller and mid-size volumes, and for the typical Power BI workload — where reports are used repeatedly throughout the day — it delivers interactive performance without extra modeling effort. At the top end of the volume curve, the picture shifts. With billions of rows, a Composite Model with aggregations was the fastest and most consistent pattern, staying sub-100ms on queries the aggregation tables can resolve. The caveat is equally clear: that advantage doesn't extend to queries that fall through to the underlying DirectQuery source, so the payoff depends on how well your aggregations match real user behavior. These are just the headline findings — the detailed results vary considerably by data volume, cache state, filter scenario, and query type. We'd encourage you to read the white paper for the full picture before deciding on a pattern. One thing worth noting up front: this is a point-in-time comparison as of June/July 2026, and both platforms are moving quickly. It also measures the end-user query experience within Power BI, rather than raw database execution speed. Treat it as a guide for running your own testing, on your own data. Explore the white paper for a full walkthrough of through each pattern in detail — the test setup, what was measured, and how results break down by data volume, cache state, and query type. Visit the Power BI download center to access the paper and other related resources.Direct Lake Calculated Columns (Preview)
Calculated columns are now available in preview for Direct Lake on OneLake semantic models. This has been one of the most requested capabilities since Direct Lake launched and closes a long-standing gap with Import and DirectQuery storage modes. You can define calculated columns directly in your semantic model using DAX in web modeling and Power BI Desktop, without changing the table storage mode or modifying data upstream. The problem this solves Direct Lake combines Import-like performance with near real-time data freshness by querying Delta tables in OneLake and loading data into memory as needed. But until now, if your model needed a derived column, you had only two options: push the logic upstream into the data source or move the table to a different storage mode. Calculated columns close that gap – you can now define columns directly in the semantic model using DAX without leaving Direct Lake. What you can build Common use cases include: Derived values, such as an age calculated from a birth date. Concatenating fields, such as city and region into a single field for slicers. Formatted dates like Month-Year for grouping in visuals. Multilingual reports using data translations with USERCULTURE(). Personalized content based on functions like USERPRINCIPALNAME(). Examples 1. Age = DATEDIFF( DimCustomer[BirthDate], TODAY(), YEAR ) 2. Customer Location = DimCustomer[CityName] & ", " & DimCustomer[ContinentName] 3. Month Name = FORMAT( DimDate[FirstOfMonth], "mmmm", USERCULTURE() ) The first two return the same value for every user unless security context differs. The third adapts to the language of the person viewing the report – see Month Name. Calculated columns now have a new Expression Context property. Direct Lake calculated columns support User Context expression context only. With User Context: The expression is evaluated when a user queries the model. Evaluation respects row-level security (RLS) and object-level security (OLS). Expressions that do not reference user-aware DAX expressions or secured columns typically return the same value for every user. Considerations: Cannot be used in relationships. Direct Lake calculated columns are evaluated at query time and do not materialize. Because of this, they cannot be used as relationship keys. Build relationship keys in the Delta table when needed. Do not observe filter context. Calculated columns return a fixed value for each row and do not respond to report filters or slicers. Use a measure when the result must change based on report interactions. Unlike standard calculated columns, Direct Lake calculated columns are evaluated in the current user's security context. This means calculations automatically respect RLS and OLS. Security behavior across expression contexts The security difference is easiest to see with a column that references a protected value. Consider a model where OLS hides DimCustomer[Education] from a "NoEducationOLS" role, and a calculated column derived from it: Is Graduate = IF( DimCustomer[Education] = "Graduate Degree", "Yes", "No" ) The result depends on the expression context: Import - Standard Import - User Context Direct Lake - User Context Observes OLS No Yes Yes Result for a restricted user "Yes" or "No", derived from the hidden value Column not available Column not available With Standard, a restricted user still sees the derived answer and the protection is effectively bypassed. With User Context in both Import and Direct Lake, the reference to the secured column is evaluated within the user's security context, so the restricted user does not see the derived column. The sensitive value is never exposed. Import – Standard Expression Context Import – User Context Expression Context Getting Started Calculated columns for Direct Lake are available in preview. Open a Direct Lake on OneLake semantic model in the web or Desktop, create a calculated column, and begin modeling directly in DAX. To learn more, see the Create calculated columns in Power BI Desktop documentation.
TMDL View on the web: Edit semantic models as code in your browser (Preview)
TMDL View on the Web is a feature in Power BI that enables developers to view and edit semantic models as code directly in the browser using TMDL. It expands the Power BI web modelling experience by introducing a rich code editor for working with TMDL scripts—giving pro developers full transparency into the semantic model code and enabling more efficient workflows through code editing.Bringing Power BI Insights to Every Copilot User
The future of Power BI and Copilot starts by meeting users where they already work. We’re bringing trusted Power BI answers into Microsoft 365 Copilot first, so people can ask questions of governed business data in the flow of work — then carrying that richer, more conversational experience back into the Power BI service itself.
Power BI September 2025 Feature Summary
The Power BI September 2025 Feature Summary introduces updates for users and coincides with FabCon Vienna! This release introduces several key enhancements, including, updates to Copilot and AI capabilities such as the standalone Copilot default-on experience, and important changes to default visuals like the Bing Maps Visual icon. Dive into the details to discover how these innovations can elevate your Power BI experience. Contents Events and Announcements Get certified in Microsoft Fabric Power BI DataViz World Championships – happening live at FabCon Vienna! Copilot and AI Standalone Copilot to default-on Auto-selection of Copilot workspaces Save Explorations to pro workspaces Find Power BI reports in M365 Copilot search improvements Prep data for AI coming soon to the Power BI service Reporting Enhanced DAX Time Intelligence (Preview) Performance analyzer available when editing a report in the web Translytical Task Flows are now enabled by default in Power BI Modeling Editing semantic models in the Power BI Service (Generally Available) Live editing Direct Lake semantic models with Power BI Desktop (Generally Available) TMDL view (Generally Available) Download PBIX of XMLA altered semantic models Fabric Notebooks for Power BI: Best Practices Analyzer and Memory Analyzer (Generally Available) Direct Lake on OneLake + import in web modeling (Preview) Direct Lake on OneLake + import in Desktop DAX User Defined Functions (Preview) Refresh data or schema options in Power BI Desktop Power BI content shared in Teams now opens in a separate window Mobile NFC tag support in Power BI Mobile (Generally Available) Other New Tenant Setting for Set alert button visibility Visualizations ADWISE Advanced Column v 2.0 Zebra BI Tables: Calculated Reports in One Click and Brand Images Word Cloud by Powerviz Drill Down Combo Bar PRO by ZoomCharts CAGR Arrows Now in Zebra BI Charts Closing Version number: v: 2.147.909.0 Date published: 09/15/2025 Events and Announcements Get certified in Microsoft Fabric Join the thousands of other Fabric users who’ve achieved over 50,000 certifications collectively for the Fabric Analytics Engineers and Fabric Data Engineers roles. To celebrate FabCon Vienna, we are offering the entire Fabric community a 50% discount on exams DP-600, DP-700, DP-900, and PL-300. Request your voucher. Power BI DataViz World Championships – happening live at FabCon Vienna! Four finalists are taking the stage at FabCon to compete for the title of world champion! FabCon Vienna Power BI Dataviz World Championships – and the winner is... Congratulations to Paulo Grijó! Read more about the finals and all four finalists. Copilot and AI Standalone Copilot to default-on The standalone Copilot experience for Power BI, also known as chat with your data—is a full-screen, chat-based AI experience that finds data and answers questions about any report, semantic model, or Fabric data agent you have access to. The standalone Copilot experience will be enabled by default for all tenants where Copilot has already been turned on. If you would like to opt out, If your tenant admin has enabled this setting: Users can use Copilot and other features powered by Azure OpenAI—this setting will be automatically enabled in September: Users can access a standalone, cross-item Power BI Copilot experience (preview). We understand that some organizations are still preparing their data for AI and configuring what Copilot can access. You can opt out, here’s how: Turn the setting on in the admin portal, then immediately turn it off. This action tells us that you prefer to enable the standalone Copilot later, and we’ll skip the automatic default-on for your tenant. Auto-selection of Copilot workspaces If you don’t have access to a Fabric Copilot Capacity (FCC), you can still use the standalone Copilot experience. However, you’ll need to manually select a Copilot workspace for billing and usage tracking. This step has caused confusion for many business users, as workspace names, eligibility rules, and billing details are often unfamiliar. Beginning in late September, Copilot will automatically assign a workspace to each user, allowing them to access their environment without additional steps. You will still have full control to change their selection at any time, but the automatic selection will clear a roadblock and make it easier to start getting insights from Copilot. How auto-selection works Smart distribution: We generate a partially randomized list of workspaces, weighted toward those with more available capacity. This helps balance usage and avoids overloading any single capacity. Eligibility check: We’ll pick go down that list and pick a workspace tied to a capacity that meets Copilot requirements (in short, F2 or higher, in a supported region, enabled for use with Copilot). Persistence: Once selected, the workspace stays set across sessions. Fallbacks: If the workspace is later disabled for Copilot, we’ll automatically reassign a new one and alert the user. If an FCC becomes available, it will always override the auto-selected workspace. User control: A dismissible notification will let users know which workspace was chosen, with a direct option to change it. mber_2025_Feature_Summary You can also update it anytime via More > Manage workspace in the standalone Copilot experience. Why this matters This update clears friction for business users who want to use Copilot but don’t know (or need to know) the intricacies of capacities and workspace settings. By auto-selecting a workspace, we help them get straight to the insights they care about—while still giving admins and power users the flexibility to make changes as needed. Save Explorations to pro workspaces Previously, you could only save Explorations to Premium workspaces. Now, you can also save them for Pro workspaces as well. This makes it easier to save and share insights gained during your exploration. Find Power BI reports in M365 In the July 2025 Power BI Feature Summary, we announced the extension of the Power BI and M365 integration to further improve Power BI item discovery and search relevancy in M365 Copilot experiences & Office search. This expansion will empower consumers to locate their Power BI reports and data directly from M365 environments where they already work. Since then, we’ve made significant progress; users can now find Power BI reports by searching for a variety of report content in both Microsoft 365 Search and Copilot. Now, searching for a report title, description, chart title, or other contextual details within the report will display relevant Power BI items in M365, simplifying the process of finding reporting resources for daily data-driven decisions. Search for Power BI items in the M365 Copilot Search Search for Power BI items in the M365 Copilot Chat To learn more about how to share Power BI data with M365 for your organization, refer to the Share data with your Microsoft 365 services documentation. Copilot search improvements Copilot report descriptions make it easier to identify which report can answer your question without needing to open each one for verification. When the report author hasn’t added an item description, Copilot will provide a descriptive caption in Copilot search lists. Search prefers items that have been Prepped for AI. When content creators update the Prepped for AI setting to indicate that a semantic model is ready for use with Copilot, search is now boosting that prepped content (both the model, and all reports that use it). Content that’s ready for Copilot will be preferred in Copilot search over equally relevant Certified & Promoted content. In addition, we’ve sped up the delay in applying the prepped status of the model to the report from 24 hours to under 1 hour (but usually just a few minutes) in most cases. Hints for item types and workspaces, Copilot search returns results that are semantically like your question’s topic, which can be helpful when you don’t quite remember the report’s name. But often we remember other information that could help narrow the search. Copilot can now recognize the key concepts of workspaces and item types, which you can use to guide search. If you’re looking for a semantic model you created ages ago to model effective advertising spend, you might ask: ‘Find semantic models with fields about campaigns, ROI, and impressions'. Or, if you want to prefer content in a particular location, you might say: ‘Summarize quarterly sales, from the workspace East Coast Only’. This won’t act as a strict filter, so if you have a workspace called ‘Excluding East Coast’, you might see results from that workspace because the workspace names are similar. Copilot search responses will now prefer to surface just reports and data agents when the user doesn’t specify. Copilot can still use the report’s semantic model to answer the user's question, but in this way, we’re focusing on items that users are more likely to recognize. Updates to support filter pass-through, you may have already noticed updates in how verified answers show up in our search lists. These changes are purposeful and support Copilot in honoring filter context. For example, when a question about tourism on O’ahu is submitted, it is useful if search indicates that someone has already verified the answer to a similar inquiry. If information is needed for a different island, and that selection is available as a filter in a commonly used report, Copilot can be directed to use that specific report. In the following example, the verified answer is used as a starting point but filtered to directly answer my original question. You can find the filters applied to the visualization. When you use Copilot to search, you'll now see recommendations for what to do next, such as summarizing the report or providing an overview of the key metrics. Learn more about these features and how Copilot search works in the Find content with Power BI Copilot search documentation. Prep data for AI coming soon to the Power BI service In the coming weeks you will be able to prepare your data for AI directly in the Power BI service. Making it easier to keep your semantic models Copilot-ready without switching tools — and it unlocks additional model types you can prepare, including Direct Lake models and more. With prep data for AI features available in the service, you will be able to: Select a Copilot schema Set up and manage Verified Answers Add AI instructions To use these features: In the Power BI service, select the semantic model you want to prep. On the model page, select the Prep data for AI button in the ribbon. When you’re ready, don’t forget to update the model setting so users in your organization can start using Copilot with confidence. Reporting Enhanced DAX Time Intelligence (Preview) A brand new, calendar-based approach to time intelligence in Power BI has arrived! With this update, you can now define custom calendars—such as fiscal years or 4-5-4 retail calendars—directly in your data model. This gives you precise control over how your data maps over time, enabling more accurate and flexible analysis. What’s more, it allows you to do week-based calculations as well! Basic example using a Gregorian calendar How to use calendars to perform a total month-to-date calculation on a Gregorian calendar: To get started, simply turn on the 'Enhanced DAX Time Intelligence' feature in preview settings. Select Calendar options from the context menu on your date table. Create a calendar by associating columns in your date table into categories. Example: The Gregorian Calendar below maps the Year, Quarter, Month, Month of Year and Date categories to primary and associated columns (Columns can be named as desired). Perform calculations based on your calendar. Example: If you have a calendar called ‘Gregorian Calendar’ defined in your model, you can use TOTALMTD to calculate a month-to-date total sales value based on that: Sales MTD = TOTALMTD ( [Total Sales], 'Gregorian Calendar' ) In addition to expanding existing functions with support for calendars, we have also added brand new functions that allow you to do week-based calculations as well, such as TOTALWTD, PREVIOUSWEEK and more. Show your result in a visual. Example: This chart shows the Total Sales and Sales MTD value we calculated previously. Working with fiscal calendars Many calendars, particularly fiscal calendars, are shifted Gregorian calendars, in which the year does not being on January 1 st , but for example on July 1 st . Microsoft is an example of a company that uses a shifted fiscal calendar. In this case, a date table would include columns for the fiscal periods, such as fiscal year, fiscal quarter and fiscal month: Now, you can define a Fiscal Calendar: endar You can use the calendar in our calculations, for example, this calculates the SAMEPERIODLASTYEAR value using the Fiscal Calendar: Sales Same Period Last Fiscal Year = CALCULATE ( [Total Sales], SAMEPERIODLASTYEAR( 'Fiscal Calendar' ) ) This can then be visualized as follows: Week-based calculations As mentioned, you can now also perform week-based calculations, including 454 and other patterns. After making sure your data table contains week information, associate the relevant categories in your calendar as done below for a 454 calendar: Next, create your DAX calculation, for example, a week-to-date calculation can be made using TOTALWTD: Sales WTD 454 = TOTALWTD ( [Total Sales], 'RETAIL-454' ) The column chart shows the actual and the week-to-date sales value based on our RETAIL-454 calendar. There is much more to learn about this feature as it allows for a lot of advanced scenarios. Learn more about this preview in our time intelligence documentation and try it out in your next report and let us know what you think! Performance analyzer available when editing a report in the web Performance analyzer is now available in the web report editing experience and provide information on visual load times. Load times update as you interact with the report. Copy the DAX query from any visual to troubleshoot even further. Previously accessible in Power BI Desktop, this feature now allows users to observe report performance after publication. To learn more, refer to the Use Performance Analyzer to examine report element performance in Power BI Desktop documentation. Translytical Task Flows are now enabled by default in Power BI As a refresher, Translytical task flows, released in May 2025, marked a major evolution in Power BI by allowing users to act on insights instantly without leaving the report. Powered by Fabric User data functions, Translytical task flows allow users to automate tasks such as updating records, dynamic notifications, and even triggering workflows across other systems. To learn more about Translytical task flows, refer to the Understand translytical task flows documentation. Modeling Editing semantic models in the Power BI Service (Generally Available) This milestone unlocks end-to-end Power BI authoring directly in the browser, bringing core modeling parity between the web and Desktop experiences. Yes, that means Mac users can now model in Power BI, no Desktop required! What’s Supported? Create from scratch in the web - You can create net new import semantic models and reports directly in the browser! Navigate to the ‘Create’ page and select ‘Get data’. Choose from over 100 supported connectors to bring in your data, shape it with Power Query, build your semantic model, and design your report. Edit existing semantic models - The Power BI service now offers advanced modeling capabilities, including: Adding new import tables to your model Transforming import tables using the full Power Query editor Refreshing schema and data Managing relationships Writing and editing DAX measures, calculated columns, calculated tables, and calculation groups Editing properties in the properties pane Defining and assigning row-level security roles This release enables core modeling features in both Power BI Desktop and the web, allowing you to build and manage models easily from anywhere. To learn more, refer to the Edit semantic models in the Power BI service documentation, or the Deep Dive into Editing Semantic Models in the Power BI Service (Generally Available) blog post. Live editing Direct Lake semantic models with Power BI Desktop (Generally Available) This capability allows you to use the familiar Power BI Desktop interface to edit Direct Lake semantic models. All processing occurs in your Fabric workspace, directly against OneLake data, using the Power BI Analysis Services engine instead of your local machine. With live edit, every change you make, whether creating new measures, adding calculation groups, defining relationships, running DAX queries, and more, is applied directly to the semantic model in Fabric, ensuring a seamless, scalable modeling experience. Getting started is easy You can begin in Power BI Desktop or from the web: Start from Desktop Open the ‘OneLake data hub’ in Power BI Desktop. Select your Direct Lake semantic model. From the ‘Connect’ button drop-down, select ‘Edit’. Start from the web: In the web experience, select ‘Edit in Desktop’ for the Direct Lake semantic model you have opened. This will launch Power BI Desktop with the semantic model ready for editing. To learn more, refer to the Direct Lake in Power BI Desktop documentation, or the blog post. TMDL view (Generally Available) TMDL view introduces a modern code-first editing experience for Power BI semantic models using the Tabular Model Definition Language (TMDL). A user-oriented modeling language designed to enhance transparency, governance, and efficiency in the development of semantic models. With TMDL view, you can easily make batch updates using simple find-and-replace operations or leverage your preferred generative AI tool to create or modify TMDL code at scale. General availability introduces several notable enhancements: Full code highlighting including DAX and M (Power Query) Execution status in the script tabs For more information about TMDL view and full list of capabilities, please refer to our Work with TMDL view in Power BI Desktop (preview) documentation. Download PBIX of XMLA altered semantic models A key goal of the TMDL view work was to ensure Power BI Desktop can reliably handle any semantic model configuration. If the model is valid in Analysis Services in a Fabric workspace, it can be opened and edited in Power BI Desktop without crashing. Semantic model metadata not accessible through the user interface - such as multiple table partitions - can still be edited using TMDL view. Previously, users could use the XMLA endpoint with external tools to make semantic model changes - such as creating multiple partitions - that were supported by Fabric but not by Power BI Desktop. This mismatch often caused Power BI Desktop to crash, which is why downloads were blocked for XMLA altered semantic models. Now that TMDL view is generally available, we’ve removed this limitation. You can now download PBIX files for semantic models modified through the XMLA endpoint, and open and edit them in Power BI Desktop. This update does not mean that all semantic models are now downloadable as PBIX files. For example, semantic models with incremental refresh partitions are still not supported for download, this will be addressed in a future update. For more details on PBIX download limitations, please refer to our Limitations when downloading a report .pbix file documentation. This feature is currently rolling out and may not be fully available in all regions or for all users yet. We appreciate your patience as we complete the deployment over the coming weeks. To learn more, refer to the Open and edit any semantic model with Power BI tools blog post. Fabric Notebooks for Power BI: Best Practices Analyzer and Memory Analyzer (Generally Available) These one-click experiences make it easy to use Fabric Notebooks and Semantic Link to analyze your semantic models directly on the web. Best Practice Analyzer evaluates models using more than 60 rules across five categories: performance, DAX expressions, error prevention, maintenance, and formatting. It provides guidance on design and performance based on these criteria. Memory Analyzer provides detailed memory and storage statistics for tables, columns, hierarchies, partitions, and relationships, helping you identify optimization opportunities. We would like to give a special shoutout to the Power BI community members whose contributions laid the foundation for these tools: Daniel Otykier – creator of Best Practice Analyzer in Tabular Editor Marco Russo – developer of VertiPaq Analyzer Michael Kovalsky – builder of semantic link labs powering these notebooks Explore the Power BI Community Notebooks Gallery to discover and share notebooks that enhance data analysis and reporting with the Power BI Community. Learn more about using notebooks with your Power BI semantic models including details on this feature and its limitations in the Use notebooks with a semantic model documentation. Direct Lake on OneLake + import in web modeling (Preview) Semantic models edited in web modeling now have full flexibility of both Direct Lake on OneLake and import table storage modes. Open a semantic model with either Direct Lake tables or import tables and add in additional tables from either storage mode. Choose Get Data to add in import tables from any of the 100s of connectors supported. Choose OneLake catalog and add in Direct Lake tables from any of the Fabric data sources you have access to, including Lakehouses, Warehouses, Mirrored databases, Mirrored Azure Databricks catalogs, and SQL databases in Fabric. Summary Once in import storage mode you can transform the table further in Power Query and add in calculated columns to get your reporting where it needs to be. Hierarchies added to import tables also can be used in Analyze in Excel. To learn more, refer to the Direct Lake overview documentation. Direct Lake on OneLake + import in Desktop Power BI Desktop can also live edit semantic models with both Direct Lake and import tables. Edit relationships, add measures, and adjust column and table properties right in Power BI Desktop. To learn more, refer to the Direct Lake overview documentation. DAX User Defined Functions (Preview) Power BI has long supported custom functions in Power Query, however now DAX User Defined Functions (UDFs) provide similar capabilities. DAX UDFs allow you to define custom functions with parameters, just like you would define functions or methods in programming. Instead of copy-pasting chunks of logic across multiple measures, you can now write your logic once and reuse it everywhere. Complex problems can be encapsulated by multiple reusable functions. Functions can even refer to other functions! This way, your logic becomes easier to write, understand, maintain and debug. Whether you are working on complex models or just want cleaner, more maintainable code, DAX UDFs are for you. Up to this point, the reusability of DAX logic was limited to calculation groups. DAX UDFs, however, unlike calculation groups, can be parameterized. Getting started with DAX UDFs To get started, simply turn on the ‘DAX User Defined Functions’ feature in the preview settings. You can define DAX UDFs in multiple ways, including the DAX Query View and TMDL view. Defining and using a function Defining a function is straightforward as we have introduced a new FUNCTION keyword. The general structure for defining a function is: /// [function description] FUNCTION <FunctionName> = ( [parameter name] : [parameter type] ) => <body> For example, here is a DAX query that defines and evaluates an extremely simple function that applies a 10% tax to an amount. DEFINE /// AddTax returns the amount including tax FUNCTION AddTax = (amount) => amount * 1.1 EVALUATE { AddTax(11) } // Return 11 After adding the function to the model, you can then call the function from other places where you can use DAX, such as measures: Parameters Just like built-in functions, DAX UDFs can take zero or more parameters. You can also provide the type of the parameter, so your functions are much more resilient. For example, to identify that our AddTax function expects a numerical value, we could write. DEFINE /// AddTax returns the amount including tax FUNCTION AddTax = (amount: numeric) => amount * 1.1 Parameters can not only take scalar values but also accept tables and even expressions. Type checking To make DAX and TMDL/TMSL more consistent, we have introduced a set of new functions to do type checking and updated the DATATABLE, CONVERT and EXTERNALMEASURE functions have been updated to work with all synonyms as well. For example, we now have added ISSTRING, which is an alternative to, ISTEXT and ISNUMERIC which is a complement to ISNUMBER. A complete list is available in our documentation. Managing DAX UDFs Functions are shown in the model explorer: In DAX Query View, we even added quick queries, so it’s even easier to define and evaluate existing functions or write a brand new one. The possibilities are endless DAX UDFs open a whole new spectrum of options, and this blog cannot do it justice. We encourage you to enable the preview today and try it out for yourself. Read more in the Power BI DAX User Data Functions documentation. Please let us know what you think. We are looking forward to seeing all the creative uses of UDFs! Refresh data or schema options in Power BI Desktop When you select ‘Refresh’ in Power BI Desktop, it always performs a schema sync first, followed by a data refresh. While this behavior is convenient in most cases, there are scenarios where you may want to refresh the data without updating the model schema, even if the data source has changed its schema. For example, in Direct Lake semantic models, the underlying Lakehouse table might have changed (e.g., a new column added). You may want the latest data but prefer not to bring new columns into the model. With this month's update, you now have more control over the refresh operation. You can choose to: Sync schema only – Updates the semantic model to reflect the data source structure (e.g., column type changes or new columns). Refresh data only – Loads fresh data while preserving the current schema in your semantic model. These options are also available when you refresh tables individually in the data pane: This added flexibility helps you manage your models refresh operations more intentionally, based on your specific needs. For more information about Power BI Desktop refresh, refer to the Data refresh in Power BI documentation. Power BI content shared in Teams now opens in a separate window In this month's update, when you open a Power BI item which was shared with you in Teams chat or channel, it now opens in separate window—so your chat and other Teams apps stay exactly where you left them. Previously, opening an item from a Power BI preview card would replace your Teams chat, making multitasking difficult. With this update, items shared in a chat open in a separate window, while your original chat remains visible in a collapsible side panel. You are now able to access data, maintain ongoing conversations, and utilize additional Teams applications simultaneously. Figure - A user selects 'Open' on a Power BI report preview card within a Teams chat. The report launches in a separate Teams window, while the original chat remains accessible in a collapsible side pane. To learn more about Power BI preview cards in Teams, refer to the Link preview cards in Microsoft Teams chats and channels documentation. Mobile NFC tag support in Power BI Mobile (Generally Available) Imagine being able to access your important data just by tapping your device on a small tag. That’s the power of NFC (Near Field Communication) tags. NFC Tag Support is now generally available in the Power BI Mobile app on supported devices! This feature allows you to register and read Power BI items such as reports, scorecards, dashboards, or even a set of items like an app or workspace on NFC tags directly from the app. With NFC you can create a seamless connection between your data and the physical world. For example, a retail manager could quickly access inventory data by tapping their phone on an NFC tag placed on a storage shelf. This feature is especially useful for frontline workers who need quick access to data while managing retail floors, inventory, or manufacturing processes. Getting started is easy: open the Power BI Mobile app, navigate to the item you want to register, press the Register to NFC button in the 3 dots menu, and follow the prompts to link it to an NFC tag. Once you’ve registered your desired item to the tag, anyone with the Power BI Mobile app can get to the item simply by tapping the tag with their device, whether the app is open or not. If the user doesn’t have permission to access the item, they’ll be taken to the request access flow. NFC tags are affordable, flexible, durable, and reliable, and can easily be reused. To learn more about NFC support in Power BI mobile, refer to the Connect data to physical locations with NFC tags documentation. Other New Tenant Setting for Set alert button visibility A new tenant setting, all Power BI users can see ‘Set alert’ button to create Fabric Activator alerts, is rolling out this week. This setting will give admins more control over which users can view the Set alert button, which allows users to create Fabric Activator alerts on their visuals, sending real-time notifications based on predefined data conditions. When enabled, all Power BI users will see the ‘Set alert’ button in reports. When the setting is turned off, the button will only be visible to users with tenant-level Fabric access, which was the group of users who could see the button prior to this change. Regardless of whether the setting is turned on or off, only users with permission to create Fabric items can set up Fabric Activator alerts. The benefit of turning this setting on is that it allows users for whom Fabric was enabled for only specific capacities to also set alerts, unlocking the power of real-time alerting for more Power BI users. This setting is currently disabled and will be turned on by default the week of October 13th. Visualizations ADWISE Advanced Column v 2.0 Advanced Column is easy to use column chart for comparing one or more values with clearly interpretable difference lines. It is best suited for comparison of values between time periods, categories or quantities. This visual presents the following features: Chart types - stacked, clustered and nested/chimney charts in one visual. Difference lines – lines to clearly show difference above compared columns with values in specific shapes, all configurable (percentage/absolute difference, colors, borders, rounded corners, lines share starts/ends). Top N selection Built in – Easily display key data by selecting the Top N columns or Top N segments within each column + the "rest" part of the data. Total Column - It is not necessary to display separate KPIs for totals, as the Total column is already included in the chart. User controls – Enable/disable viewer change of Top selections (how many to show, highest/lowest) and Total Column calculation. Enable and Add Icons – Icons make charts easier to read by visually representing column categories, you can add icons directly in the visual using the built-in icon picker. And other formatting - Axis Y break, thousand and decimal separator, interaction with other visuals, empty data screen, animations, gradient background, shadows, transparency. Try from AppSource. Zebra BI Tables: Calculated Reports in One Click and Brand Images The latest update to Zebra BI Tables introduces two powerful features that streamline report building and enhance data storytelling: row calculations from the data model and brand images in rows. Check out the demo video: Zebra BI May 2025 Update: One Click P&L and Brand Logos in Zebra BI Tables With the new zero-click reporting functionality, users can now define calculation logic (such as invert, result, skip) directly in the Power BI data model. Simply add a column to your dataset, define the logic with symbols (“=” (Result), “/” (Skip), “-” (Invert)), and with a single drag and drop add it to Zebra BI Tables. The column values will automatically be applied as calculations on the visual, eliminating the need for additional manual setup. It makes the creation of reports like P&Ls, balance sheets, inventory tracking, SaaS metrics, or sales dashboards dramatically faster and more accurate. Zebra BI Tables now also supports adding brand images instead of row labels. Especially valuable for consumer goods and retail companies, this feature makes reports more intuitive and engaging. By instantly recognizing brand logos, end users grasp insights faster and spend less time searching for context. These updates contribute to: Massive time savings. Error reduction. Standardized reporting across teams. Simplify your reporting with Zebra BI Tables and share your feedback. Word Cloud by Powerviz The new Word Cloud by Powerviz is available, an advanced visual which empowers you to create some of the most high-quality and creative word art in the Power BI. Key Features: Word Styling: Make your word clouds pop with personalized text styles. It offers font styling, direction & text editing features. Color Options: Choose from 30+ color palettes, including color-blind safe options. Shapes: Create eye-catching word clouds by selecting or uploading images. Exclude: Easily remove unnecessary words and symbols from the text to produce a clean and focused word cloud. Ranking: Filter out Top/Bottom N Words. Conditional Formatting: Easily spot words with dynamic rules. Lasso/Reverse Lasso: Select or deselect multiple words with ease. Grid View: Switch to an interactive table with sort, filter, and search features. Show Condition: Dynamically show or hide the visual based on conditions. Ideal for marketing, education, market research, and presentations—use it for sentiment analysis, SEO keywords, brainstorming, surveys, and engaging communication. Try Word Cloud visual for FREE from AppSource Check out all features of the visual: Demo_file Step-by-step instructions: Documentation YouTube Video: Video_Link Learn more about visuals: https://powerviz.ai/ Follow Powerviz: https://lnkd.in/gN_9Sa6U Drill Down Combo Bar PRO by ZoomCharts What makes Drill Down Combo Bar PRO the best custom visual for visualizing categorical data? It’s all about the drill downs – in Combo Bar PRO, you can create a hierarchy of up to nine category fields, and users can easily drill down by clicking directly on data. Deeper, more focused insights, but only when the user needs them. The visual is designed to provide top-notch user experience: the slick and intuitive on-chart interactions, the smooth animations, the seamless cross-filtering with other visuals, and full touch support all make Combo Bar PRO a crucial addition to your next report. And the best part? Combo Bar PRO supports up to 25 series, and each series can be visualized as bars, lines or areas. With a wide variety of customization options, you can create the perfect chart for your use case. We also recently published a guide on how to create different types of stacked charts with Combo & Combo Bar PRO, including stacked bar, stacked & clustered bar, bar & line, nested bar chart and more. For a more details, refer to our blog - Power BI Stacked Column Charts: A Full Guide! Get Drill Down Combo Bar PRO CAGR Arrows Now in Zebra BI Charts Compare multi-year trends across business units, products, or regions — instantly. The Compound Annual Growth Rate (CAGR) is a critical metric for visualizing growth trends in financial analysis, strategic planning, and performance comparison. Now available in Zebra BI Charts for Power BI, CAGR arrows make it easier than ever to communicate multi-year trends directly within your reports. They are especially useful in dashboards that track long-term results, helping users highlight growth patterns and shifts over time. When used in small multiples, CAGR arrows allow immediate comparison of performance across regions, product lines, or business units — all while maintaining a shared Y-axis for IBCS-compliant reporting. Each CAGR label includes a color-coded action dot — green for growth, red for negative — with the size scaled to reflect magnitude, offering an intuitive visual cue for trend strength. To simplify reporting even further, Zebra BI Charts automatically calculates the CAGR based on your underlying data. CAGR provides a smoothed view of performance over time, helping teams refine growth targets, align KPIs, and deliver executive ready insights with clarity and impact. To learn more, refer to Introducing CAGR arrows in Zebra BI Charts. Closing This concludes this month’s update. We hope the information provided in this update is useful. If you installed Power BI Desktop from the Microsoft Store, please leave us a review. As always, keep voting on Ideas to help us determine what to build next. We are looking forward to hearing from you!
