Businesses need to manage their payroll processes in an efficient manner which helps them achieve compliance standards and maintain accurate records and keep their employees satisfied. Implementing a new payroll system requires specialized knowledge because it involves complicated procedures.
The payroll process represents a critical yet time-intensive task that growing companies must manage. Small teams face difficulties with payroll work because it requires them to calculate employee wages and handle deduction management and tax compliance.
Organizations now need to manage their personnel operations as they need to manage their financial and operational activities. Organizations are continuously seeking methods to enhance employee productivity while they optimize their human resource activities and develop a better workforce.
As organizations expand their operations, they encounter difficulties in handling employee management and payroll responsibilities and compliance requirements and workforce planning activities. Businesses today need a unified solution that simplifies human resources operations while improving productivity and decision making.
Payroll is one of the most critical functions in a business. A tiny mistake can have a ripple effect on employee trust, compliance, and cash flow. This is precisely the reason why Managed Payroll is considered a wise choice for companies that look for precision without operational tension.
When you think about how to manage a workforce today, many people assume it finishes with HR policies or payroll cycles. However, managing people today is really about how well we allow our systems to help employees and make decisions — this leads to the overall success of your employee’s growth.
Modern-day businesses need intelligent, quick, and well-connected systems for managing their staff, salary and performance. This is the point where Dayforce features have a significant influence. By creating a single solution for human capital management, they integrate HR, payroll, and talent processes of companies in real-time.
Workspace outbound access protection (OAP) helps you control where data in a Microsoft Fabric workspace can flow. The initial preview for Power BI reports, launched in June, required a report in an OAP-protected workspace to use a semantic model in that same workspace. Customer feedback highlighted that this was too restrictive. With this improvement, a report can now query a semantic model in another workspace provided a workspace administrator explicitly allowed that destination through an OAP exception policy. Apply exception policies to allow report-to-model connections OAP continues to block outbound report-to-model connections by default. When a report opens, Power BI evaluates the report workspace policy before it renders the report in the browser. If the destination workspace is covered by an applicable exception, the report can connect to its semantic model. Otherwise, Power BI blocks the connection, and the report does not open. The report honors the policy that a workspace admin configured for the semantic model destination. You don't configure an exception on each report, and you don't need to move the report and semantic model into the same workspace. The OAP exception policy supports a common Power BI architecture: a central team manages shared semantic models in one workspace, while business teams build reports in separate workspaces. You can preserve that separation of ownership without removing the outbound boundary from the report workspace. See the improvement in action The following example shows a report stored in an OAP-protected workspace, and its semantic model is stored in another workspace. First, the report does not have an applicable exception policy. Power BI blocks the cross-workspace connection and displays the following error because the report can't access its semantic model. Figure: OAP continues to block outbound report-to-model connections by default. Next, a workspace admin creates an exception policy for the semantic model workspace. In the workspace settings under Outbound networking, select Add new cloud connection rule, select Power BI Semantic Model as the Connection Kind, and select the desired semantic model workspace under Workspace exception, as in the following screenshot. Select Add, and then select Save to save the Data Connection rules. Figure: An OAP exception policy to allow report-to-model connections. After the policy takes effect, the same report loads and its visuals render successfully. The report binding doesn't change. The OAP policy determines whether the cross-workspace connection is allowed. The semantic model remains subject to its own OAP controls. Connections from the semantic model to cloud databases, on-premises systems through gateways, lakehouses, warehouses, and other sources are still evaluated against the semantic model workspace's data connection rules. Make sure you enable OAP for both, the report workspace as well as for the semantic model workspace. Next steps Work with your workspace admin to confirm that your report workspace meets the OAP prerequisites and that OAP is enabled. Then create an exception policy for each approved semantic model destination. Policy changes can take about 15 minutes to propagate. For configuration details, refer to the Workspace outbound access protection for Power BI reports documentation. To understand downstream enforcement, refer to Workspace outbound access protection for semantic models.
About this series This is the first in a six-part Power Query Corner series exploring the new Power Query experience. Each post takes a closer look at a different part of the experience, including what’s changing, why it matters, and how you can put it to work. Getting data doesn't always begin with a connector name. You might know which database to use, recognize a team-maintained Fabric item, want to return to a source from yesterday, or already have the query logic you need. A connector list is useful once you've decided how to connect. But choosing the right data often comes before that decision. We moved to a module-based approach so Get data can support those different starting points, rather than making every task begin with the same connector picker. The idea is simple: start with what you know, then follow the route that fits the task. Modules organize discovery, reconnection, and authoring around that idea. They don't remove the need to authenticate, select the right objects, inspect a preview, or maintain the query afterward. This first Power Query Corner issue follows a sales-report scenario in the new Power BI Desktop experience. It also uses clearly labeled Power Query Online examples to explain the wider design, then looks at the five most frequently reported Get Data problems and the work addressing them. The customer-feedback analysis draws on publicly available reports in our community forum thread, where we track feedback on the new Power Query experience. Choose a Get data route that matches your task Priya is preparing a regional sales review. A colleague offers a spreadsheet export, but the team also maintains sales data in Fabric. Before choosing Excel or another connector, she needs to decide whether to reuse that maintained item, return to a known source, or establish a new connection. A module is a task-focused view inside Get data. Home brings the available routes together; the other modules give each task room for its own search, context, and actions. In Desktop, that includes New, Recent data, OneLake catalog, Blank table, and Blank query. The names and choices offered depend on the product hosting Power Query. Figure: Home brings different starting points into one Get data experience. View more opens the corresponding full module; a source shortcut starts that source's connection flow. Official Desktop documentation screenshot. Source: Microsoft Learn Know the source? Keep the direct route. If Priya already has the required server, file location, or service URL, New remains the straightforward route: search for the connector or browse its category, then supply the required settings. Home can provide a shortcut without first opening the full list. Selecting a connector starts the connection workflow; it doesn't immediately load data. This matters for familiar work. The module-based approach isn't an instruction to browse every module before choosing a CSV file. It should preserve a direct path for someone who already knows the source. Know the business data? Discover the item first. If Priya knows the team maintains sales data but doesn't know its endpoint, OneLake catalog gives her a different starting point. She can find an item by its business context, then review its type, owner, location, and available endorsement or sensitivity information before deciding to connect. Imagine two items, both named Sales: one is in the team's maintained reporting location, while the other belongs to a personal test project. The name alone isn't enough. Catalog context helps Priya ask the right questions before she commits the report to a source. Endorsement is a useful signal, not a guarantee of suitability, and discovering an item does not grant permission to read it. The benefit is not merely another way to open the same dialog: it lets Priya choose an appropriate existing data item before looking up connection details or creating another export. To learn more, refer to the OneLake catalog overview for the catalog's broader discovery, governance, and security roles. Used it before, or need a small starting table? Recent data is the route back to a source Priya already recognizes. It avoids starting the decision again at the connector list, but a recent entry isn't a snapshot of the data or a guarantee that its location and permissions are unchanged. Blank table and Blank query answer a different question: what if the starting point isn't an external source? Priya might enter a small RegionCode-to-RegionName mapping in Blank table or paste a self-contained M expression into Blank query. M is Power Query's formula language. Entered values become part of the query; pasting a spreadsheet's values does not create a refreshable connection to that spreadsheet. Power Query Online examples, not Desktop capabilities The broader module design also accommodates finding a source by browsing the place where it lives. Recognizing an Azure resource or a SharePoint site is different from knowing its server address or file URL. Where those source-browsing experiences are offered, they can carry the user from a recognizable location to the contents they want. Browsing into a location and selecting it for a connection are different actions, and a file's contents are different from a folder's file list. Browse Azure, SharePoint browsing, and Upload is not currently available as modules in Power BI Desktop. They are part of Dataflow Gen2, and some are also available in Power BI web modeling; the available modules vary by host. There is no committed release date for these modules in Power BI Desktop. This module distinction should not be confused with the availability of individual Azure or SharePoint connectors through New. Search scope, filters, previews, and available actions depend on the browser and host. The useful principle is to support recognition and navigation where appropriate while retaining direct connector configuration. Dataflow Gen2 illustrates another distinction: reusing data is not the same as reusing query logic. OneLake catalog helps find a data item; My Queries holds personal M scripts; Shared queries (Preview) let authors import logic shared by others. For example, Priya could reuse an existing region-cleanup script in a dataflow instead of recreating those transformations. Importing shared logic creates an independent copy, not a live link to its original, and does not transfer credentials or destinations. To learn more, refer to the My Queries or Shared Queries documentation. Figure: Dataflow Gen2 example, not Power BI Desktop: My Queries is a personal library of query logic, distinct from recent sources and from the separate Shared queries module. This published Dataflow Gen2 screenshot illustrates why different tasks need different entry points. Source: Microsoft Learn Modules can also support tasks such as describing transformations with Copilot in Dataflow Gen2, subject to that feature's requirements. That does not make every Power Query Online module a Desktop capability. Use Get Data in Dataflow Gen2 for its supported entry points and Data sources in Power BI Desktop for Desktop. Try it: Choose and preview a sales source in Power BI Desktop or web modeling You can use the October 2026 release of Power BI Desktop or try Power BI web modeling today with an authorized source in a nonproduction report. In Desktop, enable the preview: navigate to File > Options and settings > Options > Preview features, select New Power Query experience, and select OK. The exercise below is a workflow, not a supplied sample dataset. For the documented preview prerequisite, refer to the Data sources in Power BI Desktopdocumentation. Power BI web modeling uses Power Query Online, not this Desktop toggle. Define the decision: Priya needs sales by region for the intended reporting period. In Desktop or Power BI web modeling, choose a maintained item in OneLake catalog, a known source through New, or an appropriate Recent data connection; the available routes vary by host. Connect with context: compare the item’s owner, type, and location, or provide the connector’s settings, then authenticate with your authorized account. Catalog visibility does not grant data access. Preview before committing where Navigator is offered, select the intended object and check its columns and level of detail. In the new Desktop Navigator, use Transform data in the Load dropdown when shaping is needed; follow the web modeling controls for that host. Check the outcome in the editor: confirm the selected query and its Source step and explain which source the report now depends on. Use the linked Microsoft Learn guidance for detailed connection steps and host-specific options. Figure: The selected item's type determines its available actions and subsequent connection path. This Desktop documentation screenshot shows Connect and Edit, not an Import/DirectQuery selector. It does not imply the same actions for every catalog item. Source: Microsoft Learn The route changes how you find the source; it does not skip the source-specific connection and preview stages. Some connectors provide a table preview rather than Navigator. For those patterns and host distinctions, refer to the Getting Data Overview. documentation. In the Power BI service, use Create > Get Data for a new semantic model, or Get data in an existing model's ribbon, with the required editing permissions. A semantic model contains the tables, relationships, and calculations used for analysis. This route is not a Dataflow Gen2 destination workflow. Refer to the Edit semantic models in the Power BI service. documentation to learn more. Compare the decision, not just the dialog layout The legacy Desktop Get Data dialog is organized around connector categories: choose the source type, then connect. That remains an effective mental model when you already know the source. Legacy Desktop also has recent-source and Fabric-data entry points; the point is not that these ideas never existed before. The new experience brings different starting points into an organized Get data surface. New starts with the connector; OneLake catalog starts with an existing data item and its context; Recent data starts with previous work; Blank table and Blank query start with values or code. Home helps choose among the available routes instead of acting as the only place where everything must fit. That changes Priya's first decision from “Which connector should I pick?” to “What am I trying to reuse or create?” For a maintained Fabric source, she can investigate the item before configuring a new source connection. For a known CSV file, she should still be able to take the direct route. In supported Power Query Online hosts, query-library and source-browsing modules extend the same principle to other tasks. A common organizing pattern does not mean identical behavior. Power BI Desktop and Power Query Online differ in how connection settings, authentication, and load or save actions work. In the new Desktop Navigator, Transform data is inside the Load dropdown; the documented legacy flow has a separate Transform Data button. Choose the transformation route when the data needs inspection or shaping before loading. For host-specific gaps and workarounds, refer to the New Power Query experience known limitations and workarounds documentatin. Some Desktop workflows still use a legacy interface while preview is enabled. The design is useful only if those routes remain practical. Discovering the right data should not come at the expense of an established SQL-editing workflow, required Web options, a reliable Combine action, or prompt access to a familiar connector. That is why the feedback below matters: it tests the intended benefits against the work people need to finish. State of the new UI Status summary The new Get data experience remains in preview. Alongside making sources easier to discover, an important part of this work is preserving the connection workflows people already depend on in the legacy experience. We've addressed the missing native-SQL input when creating connections with supported connectors. A native SQL statement is a database query supplied directly to the source, rather than a sequence authored entirely through Power Query's transformation controls. Entering that statement when first connecting and reopening it later are different workflows. Coverage for reopening connection settings through the Source step's gear icon is still partial for native SQL and other extension-based connectors. We're continuing work on the underlying connection dialog to support these editing scenarios more consistently. For the maintained reference to current gaps and workarounds, refer to the New Power Query experience known limitations and workarounds documentation. What we're hearing For this first issue, we reviewed the discussion from its beginning on May 11 through October 26, 2026: the opening post and all 386 replies available at the review cutoff. The five themes below were selected by the number of distinct contributors explicitly reporting each problem, not the number of posts or likes. A person is counted once per issue and can appear in more than one theme. These counts describe the discussion, not the proportion of all customers affected. Because this is a full-history review, the ranking includes the initial native-SQL gap that has since been addressed. We keep it separate from later editing problems so progress on one is not mistaken for completion of the other. Entering native SQL is an essential part of connecting Twenty-four distinct contributors in the first-run feedback review. For some teams, connecting to a database starts with an existing SQL statement, not simply selecting a table. That statement defines the dataset they want to bring into the report and lets them reuse a familiar database-querying workflow. One Amazon Redshift user reported that the custom SQL input was missing from Advanced options. Another explained that their BI group primarily used Redshift and disabled the preview after discovering the missing native-query field. In their established connection workflow, entering SQL was part of getting started. Removing that input meant the new dialog could not accommodate how their team already prepared report data. This was a workflow blocker, not simply a preference about the dialog's layout. We've addressed the missing input for supported connectors. That change concerns creating the connection; maintaining its SQL afterward requires separate attention. Figure: Legacy Desktop Amazon Redshift connection dialog from Microsoft Learn. Advanced options is shown collapsed; the connector documentation lists SQL statement among its advanced capabilities. This is a legacy workflow reference, not a screenshot of the preview fix. Source: Microsoft Learn Creating a query is only the beginning: people need to edit it later Sixteen distinct contributors in the first-run feedback review. In the legacy experience, users could return to a query's Source step, select its gear icon, and reopen the connection dialog to change the SQL statement. The gear icon is the shortcut for editing settings associated with that step. An Azure Databricks contributor described the difference between creating and maintaining a query: the SQL input was available when creating a connection but disappeared when reopening its settings. They relied on that dialog for quick updates to existing reports, saving time and transformation steps, and reverted to the legacy experience when it was unavailable. There is also a broader productivity concern. One detailed example explains how a team moves parameterized SQL between Power Query and DBeaver. They use reporting-period parameters so business users can change dates without rewriting SQL. Their editing workflow depends on extracting readable SQL; copying it from the Advanced Editor instead introduces M-specific quotation marks and escape sequences that must be cleaned up before it can run in the external tool. These examples show why the gear-icon workflow matters. It provides access to an editable connection form instead of requiring users to reconstruct or modify the surrounding M expression. Coverage remains partial, and we're continuing work on reopening settings for native SQL and other extension-based connectors. The parameterized-query example is a distinct scenario, not a claim that every variation is already covered. Get data needs to become usable quickly Eight distinct contributors in the first-run feedback review. For a familiar source, users often already know exactly what they want to connect to. They expect to select the connector and proceed without waiting for the rest of the discovery experience. One contributor compared their CSV workflow directly: previously, they selected CSV and chose a file; in the new flow, they waited for the interface and then selected Browse before choosing the file. Another reported delay before the connector options were even visible. The concern is therefore not only total loading time. It is how quickly someone can act on a choice they have already made. A discovery page should help someone exploring an unfamiliar source without slowing down someone returning to a familiar one. Improvements to Get Data startup and loading are expected in the December 2026 Power BI Desktop release. Advanced Web settings can determine whether a connection is possible Five distinct contributors in the first-run feedback review. Advanced connection settings are not necessarily optional refinements. A web service may require a particular request header before it will return data, or a connection may need a URL assembled from several parts. A request header is additional information sent with the request, such as a service's required authentication header. One contributor described using an X-API-Key header for a read-only service account. That configuration worked in the classic dialog, but the new dialog provided no way to enter the header. Other feedback distinguished missing custom-header configuration from the missing API-key authentication option. These are related concerns, but restoring a header input is not the same as implementing every authentication method or secure credential-storage scenario. In the legacy From Web experience, Advanced options exposed URL parts, timeout or page-wait controls, and request-header inputs where applicable. For people relying on these settings, a simpler dialog that omits a required input cannot replace the existing connection workflow. We're working on the Web API and Web Page connectors' advanced configuration to restore the missing settings. The two connectors have different purposes and applicable options, so this is not a promise that every setting belongs in both dialogs. Figure: Legacy Desktop from Web Advanced settings from Microsoft Learn. This reference shows the kinds of controls discussed in the feedback; applicability differs between Web API and Web Page. It does not show the current preview or a completed fix. Source: Microsoft Learn Combine Files needs to produce the combined contents people expect Five distinct contributors in the first-run feedback review. Folder and SharePoint Folder workflows commonly bring similarly structured files together into one table, such as monthly exports for a reporting period. The file list and the combined data are different results: the list describes the files, while the combined table contains the rows read from inside them. In the documented legacy Desktop Folder workflow, Combine & Transform Data combines file contents and opens the result in the editor. Transform Data alone opens the file list as-is. That distinction lets users choose whether to combine immediately or filter the list before combining. One report described receiving file metadata even though the preview showed file contents. Another required a second Combine Files action from the ribbon, while a SharePoint Folder report described output containing the processed files' headers rather than the expected combined data. These are different symptoms, but they interrupt the same task: turning a collection of files into a usable dataset. The expected output is the files' combined contents, not a list that still requires the user to repeat the operation or repair the result manually. We're continuing to address the reported Combine Files issues. Figure: Legacy Desktop Folder preview from Microsoft Learn. The rows shown are file metadata, not the contents of the CSV files. The Combine action begins the workflow that reads and combines those contents. This is a reference image, not a screenshot of a reported failure. Source: Microsoft Learn Beyond these five themes, contributors also raised concerns about authentication choices, catalog and Navigator completeness, recent-source behavior, custom-connector compatibility, localization, and the visibility of Load and Transform actions. We acknowledge those reports as well; appearing less frequently in this discussion does not make their impact unimportant. What you can expect The missing native-SQL input at initial connection has been addressed for supported connectors. Our ongoing work includes improving how existing connection settings reopen through the gear icon, restoring missing advanced settings in Web API and Web Page connections, and addressing Combine Files failures. For startup and loading performance, improvements are expected in the December 2026 Power BI Desktop release. That expectation applies specifically to startup and loading; we are not announcing the same release timing for every issue discussed here. Connector and workflow coverage can differ while this work progresses. An improvement to initial connection does not automatically resolve an editing problem, and progress on one Combine Files failure does not establish that every reported symptom is fixed. For current limitations and available workarounds, including when returning to the legacy Desktop experience is appropriate, see New Power Query experience known limitations and workarounds. In Desktop, you can clear the New Power Query experience preview checkbox without restarting. That fallback does not switch Power Query Online in web modeling to a legacy interface. Share your feedback Discuss your experience and share feedback in the forum: Share your thoughts on the new Power Query experience in Power BI. Propose feature ideas or vote on existing suggestions in the Fabric Ideas portal. Continue the Power Query Corner series This post is part of our six-part Power Query Corner series on the new Power Query experience. Explore the other posts in the series: Finding and connecting to data in the new experience (Preview) Understand how your Power Query query runs (Preview) Understanding query relationships with Diagram View (Preview) Review wide tables with Schema View (Preview) Read the whole recipe in Query Script View (Preview) Cluster supplier labels and rank results (Preview) Links will be added as each post is published.
If you haven't already, check out FabCon and SQLCon 2026 in Barcelona: Building the data foundation for Microsoft Copilot and Agents for a complete look at all of our FabCon Europe announcements across Fabric and Microsoft Databases. Advancing an open, interoperable semantic foundation for AI-powered analytics Today, Microsoft is pleased to affirm our commitment to Apache Ossie (incubating), a community-led effort to establish a vendor-neutral standard for exchanging semantic metadata across analytics, AI, and BI platforms. This has been a close collaboration with Snowflake, who helped found Ossie. We have heard loud and clear that customers want to enable platform-agnostic agentic experiences. Shared semantic context must be defined once and reused across platforms, enabling agentic consumption at scale, maximizing the reach of AI-powered analytics, and empowering users to leverage the best agent for the job. Power BI semantic models are key enablers of AI-powered analysis, providing humans and AI agents with governed semantic context to answer data questions quickly and confidently. Power BI semantic models have more than 38 million monthly active users and are adopted by 94% of Fortune 500 companies. Microsoft was also recognized as a Leader and Outperformer in the GigaOm’s radar for semantic layers & metric stores in 2025. We’re now bringing this wealth of experience to Apache Ossie, and we are excited to work with Snowflake and other partners to help make the project successful. Why Apache Ossie matters Until now, semantic definitions were often recreated across platforms, introducing complexity, inconsistency, and management overhead. Apache Ossie addresses this with a common specification that tools can read and write. Its goal is straightforward but consequential: define a semantic layer once and make it portable across the data and AI ecosystem, while preserving semantic meaning and governance for agentic consumption. Collaboration with Snowflake Snowflake and Microsoft serve many of the same customers, but customers don't want to choose between ecosystems. They want their data and analytics investments to work together. That makes interoperability between, for example, Snowflake Semantic Views and Power BI semantic models a shared responsibility. This layers on top of the integration work we have already done with Snowflake for writing Iceberg tables from Snowflake to OneLake, Mirrored Databases from Snowflake, using Iceberg tables with OneLake, Catalog Integration for OneLake, Power Query Snowflake connector and much more. As discussed in the Snowflake blog post and the message below from Carl Perry, VP of Analytics at Snowflake, our collaboration is currently focused on using Apache Ossie as a vehicle for cross-platform semantic-layer conversion without moving or duplicating the underlying data. Looking ahead, we’re committed to advancing the open standard by building on our deep expertise in semantic modeling by, including helping establish DAX as an Ossie-recognized query language. We also plan to help advance Ossie support for ontologies so customers can extend the business logic in semantic models beyond agentic analysis and into platform-agnostic operational intelligence. Ultimately our goal is simple: enable customers to define once, and reuse anywhere. Today, we are highlighting the following new integration scenario: converting an Ossie document into both a Snowflake Semantic View and a Power BI semantic model. This enables customers to define shared semantic context once, then reuse it across Snowflake and Fabric while retaining the agentic experiences and capabilities of each platform. Refer to Apache Ossie Microsoft Converter for more information. Building together We look forward to working with the Apache community, Snowflake, and others across the industry to create a more open and connected future for AI-powered analytics, delivering more choice and flexibility for customers. Get involved: Visit the Apache Ossie project website and repository to explore the specification and community contribution channels. Share your thoughts and feedback with us. Apache Ossie is undergoing incubation at the Apache Software Foundation. Incubation indicates that the project is working toward the governance, infrastructure, and community practices expected of established Apache projects.
Last month, we shared a packed September update alongside the European Microsoft Fabric + SQL Community Conference. Even so, the Power BI team has continued delivering new capabilities, and we didn't want to wait another month to share them. This update includes enhancements across Copilot and AI, reporting, and semantic models, helping users create richer reports, streamline workflows, and get more value from their data. Table of Contents Copilot and AI Create Power BI reports with custom visuals using skills for Fabric (Generally Available) Reporting Gantt chart (Preview) List slicer with dropdown option (Preview) Chart plot area background color (Generally Available) Auto-expand hierarchy axis with field parameter support (Generally Available) Personal bookmarks keep column widths (Generally Available) Semantic models More accurate surge protection with semantic models That’s a wrap! Copilot and AI Create Power BI reports with custom visuals using skills for Fabric (Generally Available) The Power BI Report Authoring skill now extends natural-language report authoring to custom visuals, helping teams create reports that meet specialized business and design requirements with less manual configuration. Ask the agent to add a visual, bind it to report data, apply formatting, and validate the visualization. The skill can use supported custom visuals already added to a report, including visuals imported from a file, and it can help identify an AppSource visual when the report needs a capability that core visuals don’t provide. This reduces time spent finding visual identifiers, editing report files, and troubleshooting field mappings, so report authors can focus on selecting the right presentation for the business question. Learn more in the Power BI Report Authoring skill overview and Install Skills for Fabric guidance. Reporting Gantt chart (Preview) The Gantt visual is a new core visual for Power BI reports that lets you show tasks and progress on a time-based axis. Use it to plan projects, track schedules, or compare activities across categories directly in your report. Figure: Gantt visual showing a project schedule grouped by Planning, Development, Testing, and Deployment phases from January to April 2025, with the Format visual pane open to the Visual tab. The visual includes: Plotting of bars showing the duration of each row with progress formatting and milestones to mark key -dates. Axis with custom formatting and range controls, so you can set the start and end dates, adjust the date and time format, and choose the units that appear on the axis. Bar colors cascade naturally by category, which keeps related tasks visually grouped without extra configuration. You can add more columns next to the task list to show fields such as owner, status, or duration. A zoom axis lets report readers focus on a specific window of time and then return to the full range. To try the Gantt visual, enable it in Power BI Desktop under File > Options and settings > Options > Preview features, and then restart Power BI Desktop. To learn more and try it in your reports, refer to the Gantt visual documentation. List slicer with dropdown option (Preview) The list slicer now includes a dropdown mode that makes long lists easier to navigate and active filters easier to review. Enable Show selected first to pin current selections to the top of the dropdown, eliminating the need to scroll through every item to confirm what is filtered. The button slicer also supports Show selected first, providing the same quick view of active selections in either slicer style. Figure: List slicer in dropdown mode showing selected values as dismissible pills and the Show selected first option. The dropdown carries over the formatting you've already applied to the list slicer items, and you can now customize the height and width of the dropdown drawer to fit your report layout. The search box also has more formatting options, so you can match the slicer to the look you want across background, border, and text styles. Each selection appears as a pill outside the dropdown that shows the item name and a dismiss button, so report readers can remove a value with one click. When selections exceed the available space, a count pill shows how many more values are selected, so you can see the total without opening the dropdown. When you use Select all and then clear one or more items, the slicer makes the resulting filter state explicit. Cleared values appear as Not (item) pills, showing that Power BI is excluding those values rather than including every remaining item individually. If you do not clear any items, Select all behaves like no selection and does not filter other visuals. To learn more, refer to the Slicers in Power BI documentation. Chart plot area background color (Generally Available) The plot area of bar, column, line, area, combo, ribbon, waterfall, and scatter charts now supports a single fill color and conditional formatting in addition to the existing background options. A solid color can improve visual separation, while conditional formatting can use a measure or field value to make changes in the data easier to recognize. Figure: Bar chart with the Plot area background formatting pane open, showing the new Background color and Transparency options. To learn more, refer to the Customize visualizations in a Power BI report documentation. Auto-expand hierarchy axis with field parameter support (Generally Available) Bar, column, and line charts now support auto-expand for the hierarchy axis when you add more than one column to the axis, and the hierarchy axis now works with field parameters. Figure: Column chart using a field parameter on the axis with Auto expand turned on in the X-axis formatting pane. This matches the existing auto-expand behavior in the slicer and matrix visuals, so hierarchy interactions stay consistent across your report. Add a field parameter to the axis so you can quickly switch between a single column and any combination of columns as the hierarchy, without rebuilding the visual. Report viewers can drill up, drill down, or move across hierarchy levels from a slicer, allowing them to explore the data based on the question they want to answer. The same behavior is available when viewers use Personalize this visual to change the chart’s axis fields. Figure: Selecting a field in the Category parameter slicer updates the column chart axis and the matrix hierarchy at the same time. The animation shows a report page with a Category parameter slicer, a column chart, and a matrix. When you select Country in the slicer, the column chart updates to show Sales by Country with one bar per country, and the matrix updates to show the Country level of the hierarchy. Selecting Segment or Product instead swaps the chart axis and matrix hierarchy to that field. When you make multiple selections, the hierarchy expands automatically, so a single slicer controls the fields used across both visuals without requiring other changes to the report. To learn more, refer to the Customize X-axis and Y-axis properties, Drill mode in the Power BI service and Create field parameters documentation. Personal bookmarks keep column widths (Generally Available) Personal bookmarks now preserve visual column widths, so you can return to the exact table or matrix layout you saved instead of resizing columns again. This includes reordered and resized columns, helping you maintain a consistent personal view each time you apply the bookmark. Figure: Save a personal bookmark to preserve your report’s table column widths. To learn more, refer to the Personal bookmarks in Power BI documentation. Semantic models More accurate surge protection with semantic models Semantic models now report capacity unit (CU) usage continuously during long-running background operations instead of reporting most usage when an operation finishes. This gives surge protection a more current view of in-progress consumption, so configured rejection and recovery thresholds respond more closely to actual capacity usage. The improvement is automatic and requires no settings changes. Actual capacity measurements from August 2026, when continuous CU reporting was first enabled, show that capacity intervention shifted earlier in the process. Compared with the period before enablement, proactive surge-protection rejections increased from 5% to 12%, and operations that were delayed but ultimately accepted increased from 11% to 16%. Late-stage Fabric throttling rejections decreased from 23% to 13%. These observed changes correspond to a 145% increase in proactive surge-protection rejections, a 52% increase in delayed but accepted work, and a 41% reduction in late-stage Fabric throttling rejections. Figure: Continuous CU reporting shifts capacity intervention toward proactive surge-protection rejections and accepted delays, based on actual measurements from August 2026. Continuous CU reporting exposes consumption sooner, allowing surge protection to reject more new background operations proactively and delay more on-demand work without rejecting it. As a result, fewer operations reach deeper Fabric Throttling rejection states. To learn more, refer to the Surge protection documentation. That’s a wrap! The momentum from last month continues with new capabilities that make Power BI more flexible, efficient, and powerful for both report authors and consumers. We encourage you to explore the features highlighted in this post and review the accompanying documentation to start taking advantage of them in your own solutions. We'll be back next month with more updates and innovations from across Power BI.
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. Table of Contents General Deprecation of Old File Picker experience in Power BI Desktop Copilot and AI Power BI Agentic Experiences (Generally Available) Microsoft 365 Copilot is coming to Power BI (Preview) Power BI data answers in Microsoft Copilot Chat (Generally Available) Fabric IQ Plugin in Microsoft 365 Copilot Cowork (Generally Available) Build Fabric Apps more easily in GitHub Copilot App (Preview) Enhanced Report Consumption Copilot with Fabric IQ New control for Copilot access to semantic models Remote Power BI Authoring MCP Server (Preview) Reporting New Report Ribbon on the web (Preview) Live Visual Sharing in Outlook on the web (Preview) More control and context in Power BI Home (Generally Available) Set and reset column widths in table and matrix (Generally Available) Visual calculations for small multiples (Generally Available) Design ribbon for Power BI reports (Generally Available) Slider color options for Slicer visual (Generally Available) Translytical task flows show user date function (UDF) information in button action (Generally Available) Format pane headers stay visible as you scroll (Generally Available) Pick the axis initial scroll position (Generally Available) Azure Maps geocoding improvements (Generally Available) On-object interaction improvements (Preview) Support for Fabric Apps in Org apps (Coming Soon) Changes to Power BI subscription email delivery Increased Export to Excel row limits (Coming Soon) Value selection in Narrative visual Modeling Create and edit DirectQuery semantic models in the Power BI service Approximate Distinct Count comes to Import and Direct Lake (Preview) Accelerate text searches in your semantic models with String Indexing (Preview) Introducing Full-Text Search in Power BI Semantic Models (Preview) Data connectivity New Power Query editor (Preview) Microsoft Outlook Mail connector (Preview) More flexible Data Privacy Firewall query patterns in Power BI Desktop (Preview) Mobile Mobile page indicator (Generally Available) Contact details in Info drawer (Generally Available) Developers and APIs Power BI Projects (PBIP) (Generally Available) New Purge Data option for Fabric APIs Other Data updated and sensitivity fields of Power BI report in Microsoft Teams preview card (Coming Soon) Artifact info header for Power BI tabs in Microsoft Teams (Generally Available) Third-party custom visuals graphomate matrix Drill Down Bubble PRO by ZoomCharts Commenting in view mode: introducing Zebra BI Tables+ & Charts+ Network Graph by Powerviz Hierarchical Bar Chart That’s a wrap! 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. Figure: Animated GIF showing the creation of a Power BI report based on a remote semantic model using Modeling MCP, the Modeling skill, and report 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. Figure:Screenshot of Copilot Chat integrated into the Power 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. Figure:Screenshot of 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. Figure: Microsoft Copilot Chat featuring a data answer coming from a Power BI report, cited. 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. Figure: GitHub Copilot App chat 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: Figure: Installing 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. Figure: Example New York Taxi 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. Figure: Fabric IQ enabled in Power BI Copilot report pane (viewing mode) to answer a data question with a supporting textual answer and visualization. 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. Figure: GIF illustrating how to enable Fabric IQ in Power BI Copilot report pane (viewing mode) to answer data questions. 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.” Figure: 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 Figure: Power BI Remote MCP Server configuration in GitHub Copilot App. 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: Figure: Using Power BI Remote MCP to create a Direct Lake semantic model. 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. Figure: New report ribbon on the web. 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. Figure: A live Power BI visual in Outlook on the web. 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. Figure: Share option in Power BI. Select Link to this visual. Figure: Link to this visual as part of the share dialog. 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. Figure: Before copying the link, you can configure the view in this dialog. 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. Figure: An unfurled Power BI visual in Outlook on the web. 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. Figure: Power BI Home showing two new columns for Data refreshed and Modified date. 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. Figure: Power BI Home showing new column options dropdown. 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. Figure: Set or reset the width of an individual table or matrix column from its context menu. 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. Figure: 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. Figure: The Design ribbon provides theme controls and shortcuts to page formatting settings in Power BI Desktop. 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. Figure: Apply the Dark built-in theme from the Themes gallery on the Design ribbon. 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. Figure: Slider formatting options for a date range slicer with Responsive layout turned on. When Responsive is off, handles appear as rectangular bars with Border, Width, and Height. Figure: Slider formatting options for a date range slicer with Responsive layout turned off. 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. Figure: View the workspace, function set, and data function assigned to a button in the formatting pane. 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. Figure: Expanded section headers remain visible while you scroll through formatting settings. 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. Figure: Line chart withInitial 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. Figure: Azure Maps visual displaying an all-up view of a US ZIP Code reference layer containing more than 30,000 polygons. Some ZIP Code boundaries are not displayed because the reference layer exceeds the rendering limit.Figure: Azure Maps visual showing the previous behavior after the report is filtered to Washington. Only ZIP Code polygons included in the initial feature set are displayed, resulting in an incomplete view of the state.Figure: Azure Maps visual showing the new behavior after the report is filtered to Washington. The full reference layer is re-evaluated, displaying all relevant ZIP Code boundaries for the state. 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. Figure: On the left, select Add data to open the Build flyout. On the right, manage Title and Subtitle independently from the Add 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. Figure: Adding a Fabric App item for rating an experience into an Org App and then viewing that rating experience from within 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. Figure: 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. Figure: Export data from a table visual to Excel using Data with current layout, supporting up to 500,000 rows. 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. Figure: The new value selection options in the Narrative visual. 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. Figure: 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. Figure: 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>) Figure: 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. Figure: Setting up the “stringIndexingbehavior” property to full in TMDL view in the web. 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. Figure: Setting up the “fullTextIndexingbehavior” property to full in TMDL view in the web. 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.Figure: Example of the new TEXTCONTAINS() DAX function in DAX query view. 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. Figure: Example of the new TEXTSIMILARITY() DAX function in DAX query view. 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. Figure: Screenshot of the new Power Query editor using the light theme. 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. Figure: Screenshot of the Modern Power Query Get Data experience inside of Power BI Desktop. 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. Figure: Screenshot of the Power Query editor using the Power BI dark theme. 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. Figure: Screenshot of the Query Plan dialog inside of the new Power Query editor. 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. Figure: Screenshot of the Diagram View inside of the new Power Query editor experience. 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. Figure: Screenshot of the Schema view available in the new Power Query editor. 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. Figure: Microsoft Outlook Mail connector with the Preview badge in the Power BI Desktop Get Data experience.Figure: Microsoft Outlook Mail listed among Online Services in the Power BI Desktop Get Data pane. 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. Figure: The new Power BI Desktop preview setting allows compatible cross-partition query patterns while the Data Privacy Firewall remains active. 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. Figure: 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. Figure: Two Power BI Mobile screens showing the Contoso Sales workspace and the report’s Info drawer with a clickable contact name for sending an email. 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. Figure: Open Visual Studio Code entry point 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. Figure: Power BI report preview card in Microsoft Teams chat showing report metadata, including the last refresh date and sensitivity label. 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. Figure: Power BI report in a Microsoft Teams tab with the artifact header open, displaying report metadata.Figure: Power BI report in a Microsoft Teams tab, with the setting dialog open. 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. Figure: Zebra BI Tables+ and Charts+ enable report viewers to add contextual comments to individual data points, attach supporting 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). Figure: Customize every connection, cluster, and node to build a Network Graph that truly fits your data.Figure: Go beyond connections with powerful colors, patterns, labels, formatting, and interactive controls. 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. Figure: Hierarchical Bar Chart transforms stacked period values 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. Figure: Hierarchical Bar Chart displayed as clustered columns, with period targets and variance indicators configured from the Format visual pane. 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.
This release is part of the broader ODBC-to-ADBC transition for Power Query connectors described in the Transition from ODBC to ADBC drivers in Power BI and Microsoft Fabric documentation. What’s new Existing connections in your semantic models, dataflows, and paginated reports continue to work unchanged — the migration path is currently opt-in per connection, per workspace, or per tenant. Highlights: Improved security - ADBC drivers incorporate security enhancements, such as memory safety and garbage collection. No changes to existing behavior - This transition moves away from the embedded ODBC drivers that ship with Power BI. It does not change behavior for the ODBC connector when you use a separately installed ODBC driver. Efficient large dataset support - ADBC provides a set of standard interfaces for interacting with Arrow data, which is especially efficient at fetching large datasets with minimal overhead and no serialization or copying. Supported authentication - Databricks ADBC supports OAuth (user), OAuth (M2M / Client Credentials), and Microsoft Entra ID. Connectors covered by this release ConnectorPrevious driverNew driver (GA)DatabricksSimba Spark ODBCDatabricks ADBCAzure DatabricksSimba Spark ODBCDatabricks ADBC How to try it You can test the ADBC driver now. We suggest you start soon to help ensure the eventual deprecation of ODBC and migration to ADBC runs smoothly. There are three ways to begin validating ADBC, ordered by how much control you want. 1. Opt in per connection using Implementation="2.0" The fastest way to compare ADBC and ODBC for a specific report or dataset. Add the Implementation="2.0" option to the source step in your Power Query expression: Source = Databricks.Catalogs("adb-1234567890.1.azuredatabricks.net", "/sql/1.0/warehouses/<warehouse-id>", [Implementation="2.0"]) Refresh the dataset and compare row counts, column types, and totals against your production baseline. If you want to force a side-by-side comparison against ODBC, use Implementation="1.0". 2. Override the default for a validation workspace If you want to validate several reports together, a workspace admin can turn ADBC on for a single workspace while the rest of the tenant continues to use the legacy driver. Publish the reports you want to test into that workspace and run your normal refresh schedule. 3. Enable ADBC by default at the tenant level When you’re confident with the results, the tenant admin can enable Users can connect to data sources by using Apache Arrow database connectivity (ADBC) in the Admin portal. New connections across the tenant will use the ADBC driver by default, and Desktop and the service stay aligned on the same driver. What to expect during validation The ADBC driver is designed as a compatibility-preserving replacement for the Simba Spark ODBC driver. Validate your key reports in Desktop before enabling ADBC at the tenant level and report any regressions to adbcmigration@microsoft.com. Explore Transition from ODBC to ADBC drivers in Power BI and Microsoft Fabric for more information. What’s next The Power BI service will move from ODBC to ADBC through the first quarter of 2027. We recommend that you start validating today, so the tenant-level move is a non-event when it lands. We’d love your feedback Try the new Databricks ADBC driver. If anything looks different from what you'd expect — a refresh that fails, a total that changed, a performance regression — send the tenant ID, connector, M expression, and what you observed to adbcmigration@microsoft.com. Get started this week: Read the Databricks connector documentation. Install the latest Power BI Desktop. Pick one production report on Databricks and add Implementation="2.0" to its source step. Compare row counts, column data types, and key totals against your production baseline. Report anything unexpected to adbcmigration@microsoft.com.
If you haven't already, check out FabCon and SQLCon 2026 in Barcelona: Building the data foundation for Microsoft Copilot and Agents for a complete look at all of our FabCon Europe announcements across Fabric and Microsoft Databases. More than a decade ago, I watched Power BI change the way users work, analyze and take action on their data. Since then, I have had the privilege of seeing it grow alongside our customers—from a tool for building reports into a platform used by millions of people to understand their businesses and make decisions every day. Now, Power BI is entering its next chapter. Introducing the next generation of report development We’re introducing a new app building experience in Power BI Desktop, powered by apps in Fabric, that enables users to create data applications using natural language. Starting from a trusted semantic model, users can generate, preview, edit, and publish purpose-built applications to Microsoft Fabric. These applications can accept inputs, write back data, preserve shared state, and support operational workflows, helping users move from insight to action. This experience will be available for Power BI Desktop users in the coming months. Importantly, this experience isn’t limited to Microsoft Fabric capacity customers. Apps in Power BI will be available in preview to Power BI Pro and Premium Per User customers, as well as Microsoft Fabric capacity customers. Pro and Premium Per User customers will also have access to Fabric Database capabilities, enabling them to build applications that support both analytical and transactional scenarios. This brings AI-assisted app creation to Power BI users through their existing licensing options. Our community is already bringing some creative ideas to life. Explore some examples from Microsoft and the community in the Fabric apps gallery today. Figure: Creating an app using natural language in Power BI Desktop. Figure: A community created app by Jon Sandman that shows football statistics and match replays for coaches. Expanding the semantic layer The semantic layer is an organization's most strategic asset. More than 22 million Power BI semantic models are in use every day, making Power BI the world’s most widely adopted semantic layer. Increasingly, it also grounds agents, applications, and Microsoft Copilot in that same business meaning. At FabCon Barcelona, we are sharing an early look at semantic views, allowing users to define governed business metrics and semantics directly where data lives in OneLake and reuse them across and beyond Fabric. Our goal is to bring semantics closer to where the data lives while making it open, reusable, and interoperable. We are also pleased to affirm our commitment to Apache Ossie (incubating), a community-led effort to establish a vendor-neutral standard for exchanging semantic metadata across analytics, AI, and BI platforms. Working with Snowflake and the broader industry, we’re helping customers define semantic context once and reuse it across ecosystems without duplicating data or business logic. Our collaboration with Snowflake currently focuses on cross-platform semantic-layer conversion. Looking ahead, we’re committed to advancing Apache Ossie through our deep semantic-modeling expertise, establishing DAX as an Ossie-recognized query language and expanding support for ontologies, enabling platform-agnostic operational intelligence. Figure: Semantic views provide governed business context across analytics, applications, and AI experiences. Bringing semantic models into M365 Copilot Fabric IQ in Microsoft Copilot Cowork and Microsoft Copilot Chat are now generally available. Users can ask business questions in Copilot Chat and receive trusted answers grounded in governed Power BI reports and semantic models, with Copilot inferring which report or model is right for the question. In Cowork, Power BI content participates directly in long running and asynchronous tasks. The same Microsoft Copilot experience is also coming directly to Copilot in Power BI, allowing you to use your M365 data for richer responses. Fabric IQ MCP is entering general availability, so creators can use the same conversational analytics in their own development environments and external MCP clients. You can read more details about this update in our Fabric IQ in Microsoft 365 Copilot Cowork documentation. Looking ahead Power BI’s evolution has always been shaped by the community and the millions of creators, analysts, developers, and business users who build with it every day. Your ideas, feedback, and ingenuity have pushed us to make business intelligence more accessible, trusted, and connected to the decisions that matter. Thank you for building this community—and for continuing to challenge us to imagine what comes next. You can catch all our announcements in detail in the Power BI September 2026 monthly roll-up blog. We invite you to help shape this next chapter—share your feedback with us, shape our roadmap, and meet us in person at Fabric Community Conference and Ignite!
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 mattersThe 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 changingThe 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.Figure: Switch from the semantic model settings pane to the classic settings page.Next stepsUnderstand 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.
In December, we announced the retirement of Power BI Q&A, our legacy natural-language querying experience, with retirement planned for December 2026. To give current Q&A user's additional time to assess their dependencies and transition to newer Copilot-powered solutions, we’re extending the retirement date to February 2027. This post recaps the affected experiences and provides updates on Copilot capacity availability, embedded scenarios, and sovereign clouds. Recap of the January announcement What is being deprecated? The retirement applies to both the end-user Q&A experiences, and the associated Q&A configuration tools. Retiring experience Recommended alternative Q&A in reports Copilot with Power BI reports Q&A on a dashboard Copilot standalone experience Q&A virtual analyst in mobile app Copilot in Power BI Mobile Q&A in Power BI embedded analytics Copilot for SaaS scenarios. For embedded PaaS scenarios, refer to the updates later in this post. Q&A Setup Prep Data for AI What happens at retirement? Beginning in February 2027, Q&A will no longer work in Power BI. The Q&A visual will be removed, and existing reports that contain Q&A visuals will display an error in place of the visual. Updates since December Copilot availability across capacities One of the most common questions following the December announcement was how customers relying primarily on Power BI Pro licenses could adopt Copilot capabilities after the retirement of Q&A. Copilot is now available across all Fabric capacities starting at F2. In addition, Fabric Copilot Capacity (FCC), which was initially limited to P1/F64 and above, can now be created on F2 and higher capacities. FCC is an optional way to centralize Copilot usage for assigned users, including Pro and PPU workspaces, on one capacity. Review the current Copilot requirements. This change makes Copilot available on smaller Fabric capacities, giving organizations that previously relied on Power BI Pro licenses another path to evaluate Copilot without moving immediately to a larger Premium or Fabric capacity. Embedded (PaaS) Q&A scenarios Another common question following the December announcement was whether Copilot would provide a direct replacement for Q&A in embedded (PaaS) scenarios. There are currently no plans to provide a Copilot replacement for embedded Q&A PaaS scenarios. Organizations using embedded Q&A should begin evaluating migration paths and alternative analytical experiences well before the February 2027 retirement date. Although these options are not direct replacements for embedded Q&A, customers can consider: Copilot for SaaS scenarios, for organizations that can transition from an embedded PaaS architecture to a supported SaaS experience. Narrative visual and smart narrative summaries Fabric IQ MCP Server Customers with embedded analytics solutions should review their current Q&A integrations and plan migration paths before retirement. Copilot in sovereign clouds Customers operating in sovereign cloud environments have also asked about Copilot availability following the retirement of Q&A. Copilot does not yet support sovereign clouds due to GPU availability. Organizations using Q&A in sovereign clouds should review their dependencies and contact their Microsoft account representative or support team to discuss migration options. Recommended next steps To prepare for the retirement of Q&A: Inventory existing Q&A dependencies, including reports, dashboards, mobile experiences, embedded solutions, and Q&A Setup artifacts. Identify the appropriate migration path for each dependency, using Copilot-powered experiences where they are available and meet your requirements. Review embedded Q&A implementations and evaluate supported SaaS patterns or other analytical experiences. Confirm Copilot availability in your region, particularly for sovereign cloud deployments, before selecting an alternative. Plan, test, and communicate changes before Q&A reaches full retirement in February 2027. Starting these activities early will help ensure a smooth transition before Q&A reaches full retirement in February 2027. The extension to February 2027 provides additional time to assess existing Q&A dependencies and evaluate replacement experiences. We encourage customers to begin planning their transition now, review Copilot availability and requirements, and test alternative experiences well before retirement. Taking these steps early can help ensure a smooth transition when Q&A reaches end of support in February 2027.
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.
