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The Power BI September 2025 Feature Summary introduces updates for users and coincides with FabCon Vienna! This release introduces several key enhancements, including, updates to Copilot and AI capabilities such as the standalone Copilot default-on experience, and important changes to default visuals like the Bing Maps Visual icon. Dive into the details to discover how these innovations can elevate your Power BI experience.
Contents
Version number: v: 2.147.909.0
Date published: 09/15/2025
Join the thousands of other Fabric users who’ve achieved over 50,000 certifications collectively for the Fabric Analytics Engineers and Fabric Data Engineers roles. To celebrate FabCon Vienna, we are offering the entire Fabric community a 50% discount on exams DP-600, DP-700, DP-900, and PL-300.
Four finalists are taking the stage at FabCon to compete for the title of world champion!
FabCon Vienna Power BI Dataviz World Championships – and the winner is...
Congratulations to Paulo Grijó! Read more about the finals and all four finalists.
The standalone Copilot experience for Power BI, also known as chat with your data—is a full-screen, chat-based AI experience that finds data and answers questions about any report, semantic model, or Fabric data agent you have access to.
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The standalone Copilot experience will be enabled by default for all tenants where Copilot has already been turned on. If you would like to opt out,
If your tenant admin has enabled this setting: Users can use Copilot and other features powered by Azure OpenAI—this setting will be automatically enabled in September: Users can access a standalone, cross-item Power BI Copilot experience (preview).
We understand that some organizations are still preparing their data for AI and configuring what Copilot can access. You can opt out, here’s how:
Turn the setting on in the admin portal, then immediately turn it off.
This action tells us that you prefer to enable the standalone Copilot later, and we’ll skip the automatic default-on for your tenant.
If you don’t have access to a Fabric Copilot Capacity (FCC), you can still use the standalone Copilot experience. However, you’ll need to manually select a Copilot workspace for billing and usage tracking. This step has caused confusion for many business users, as workspace names, eligibility rules, and billing details are often unfamiliar.
Beginning in late September, Copilot will automatically assign a workspace to each user, allowing them to access their environment without additional steps. You will still have full control to change their selection at any time, but the automatic selection will clear a roadblock and make it easier to start getting insights from Copilot.
How auto-selection works
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You can also update it anytime via More > Manage workspace in the standalone Copilot experience.
Why this matters
This update clears friction for business users who want to use Copilot but don’t know (or need to know) the intricacies of capacities and workspace settings. By auto-selecting a workspace, we help them get straight to the insights they care about—while still giving admins and power users the flexibility to make changes as needed.
Previously, you could only save Explorations to Premium workspaces. Now, you can also save them for Pro workspaces as well. This makes it easier to save and share insights gained during your exploration.
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In the July 2025 Power BI Feature Summary, we announced the extension of the Power BI and M365 integration to further improve Power BI item discovery and search relevancy in M365 Copilot experiences & Office search. This expansion will empower consumers to locate their Power BI reports and data directly from M365 environments where they already work. Since then, we’ve made significant progress; users can now find Power BI reports by searching for a variety of report content in both Microsoft 365 Search and Copilot.
Now, searching for a report title, description, chart title, or other contextual details within the report will display relevant Power BI items in M365, simplifying the process of finding reporting resources for daily data-driven decisions.
Search for Power BI items in the M365 Copilot Search
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Search for Power BI items in the M365 Copilot Chat
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To learn more about how to share Power BI data with M365 for your organization, refer to the Share data with your Microsoft 365 services documentation.
Copilot report descriptions make it easier to identify which report can answer your question without needing to open each one for verification. When the report author hasn’t added an item description, Copilot will provide a descriptive caption in Copilot search lists.
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Search prefers items that have been Prepped for AI. When content creators update the Prepped for AI setting to indicate that a semantic model is ready for use with Copilot, search is now boosting that prepped content (both the model, and all reports that use it). Content that’s ready for Copilot will be preferred in Copilot search over equally relevant Certified & Promoted content. In addition, we’ve sped up the delay in applying the prepped status of the model to the report from 24 hours to under 1 hour (but usually just a few minutes) in most cases.
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Hints for item types and workspaces, Copilot search returns results that are semantically like your question’s topic, which can be helpful when you don’t quite remember the report’s name. But often we remember other information that could help narrow the search. Copilot can now recognize the key concepts of workspaces and item types, which you can use to guide search.
If you’re looking for a semantic model you created ages ago to model effective advertising spend, you might ask: ‘Find semantic models with fields about campaigns, ROI, and impressions'.
Or, if you want to prefer content in a particular location, you might say: ‘Summarize quarterly sales, from the workspace East Coast Only’. This won’t act as a strict filter, so if you have a workspace called ‘Excluding East Coast’, you might see results from that workspace because the workspace names are similar.
Copilot search responses will now prefer to surface just reports and data agents when the user doesn’t specify. Copilot can still use the report’s semantic model to answer the user's question, but in this way, we’re focusing on items that users are more likely to recognize.
Updates to support filter pass-through, you may have already noticed updates in how verified answers show up in our search lists. These changes are purposeful and support Copilot in honoring filter context. For example, when a question about tourism on O’ahu is submitted, it is useful if search indicates that someone has already verified the answer to a similar inquiry.
If information is needed for a different island, and that selection is available as a filter in a commonly used report, Copilot can be directed to use that specific report.
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In the following example, the verified answer is used as a starting point but filtered to directly answer my original question. You can find the filters applied to the visualization.
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When you use Copilot to search, you'll now see recommendations for what to do next, such as summarizing the report or providing an overview of the key metrics.
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Learn more about these features and how Copilot search works in the Find content with Power BI Copilot search documentation.
In the coming weeks you will be able to prepare your data for AI directly in the Power BI service. Making it easier to keep your semantic models Copilot-ready without switching tools — and it unlocks additional model types you can prepare, including Direct Lake models and more.
With prep data for AI features available in the service, you will be able to:
To use these features:
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When you’re ready, don’t forget to update the model setting so users in your organization can start using Copilot with confidence.
A brand new, calendar-based approach to time intelligence in Power BI has arrived! With this update, you can now define custom calendars—such as fiscal years or 4-5-4 retail calendars—directly in your data model. This gives you precise control over how your data maps over time, enabling more accurate and flexible analysis. What’s more, it allows you to do week-based calculations as well!
Basic example using a Gregorian calendar
How to use calendars to perform a total month-to-date calculation on a Gregorian calendar:
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Sales MTD = TOTALMTD ( [Total Sales], 'Gregorian Calendar' )
In addition to expanding existing functions with support for calendars, we have also added brand new functions that allow you to do week-based calculations as well, such as TOTALWTD, PREVIOUSWEEK and more.
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Working with fiscal calendars
Many calendars, particularly fiscal calendars, are shifted Gregorian calendars, in which the year does not being on January 1st, but for example on July 1st. Microsoft is an example of a company that uses a shifted fiscal calendar.
In this case, a date table would include columns for the fiscal periods, such as fiscal year, fiscal quarter and fiscal month:
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Now, you can define a Fiscal Calendar:
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You can use the calendar in our calculations, for example, this calculates the SAMEPERIODLASTYEAR value using the Fiscal Calendar:
Sales Same Period Last Fiscal Year = CALCULATE ( [Total Sales], SAMEPERIODLASTYEAR( 'Fiscal Calendar' ) )
This can then be visualized as follows:
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Week-based calculations
As mentioned, you can now also perform week-based calculations, including 454 and other patterns. After making sure your data table contains week information, associate the relevant categories in your calendar as done below for a 454 calendar:
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Next, create your DAX calculation, for example, a week-to-date calculation can be made using TOTALWTD:
Sales WTD 454 = TOTALWTD ( [Total Sales], 'RETAIL-454' )
The column chart shows the actual and the week-to-date sales value based on our RETAIL-454 calendar.
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There is much more to learn about this feature as it allows for a lot of advanced scenarios.
Learn more about this preview in our time intelligence documentation and try it out in your next report and let us know what you think!
Performance analyzer is now available in the web report editing experience and provide information on visual load times. Load times update as you interact with the report. Copy the DAX query from any visual to troubleshoot even further.
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Previously accessible in Power BI Desktop, this feature now allows users to observe report performance after publication.
To learn more, refer to the Use Performance Analyzer to examine report element performance in Power BI Desktop documentation.
As a refresher, Translytical task flows, released in May 2025, marked a major evolution in Power BI by allowing users to act on insights instantly without leaving the report. Powered by Fabric User data functions, Translytical task flows allow users to automate tasks such as updating records, dynamic notifications, and even triggering workflows across other systems.
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To learn more about Translytical task flows, refer to the Understand translytical task flows documentation.
This milestone unlocks end-to-end Power BI authoring directly in the browser, bringing core modeling parity between the web and Desktop experiences. Yes, that means Mac users can now model in Power BI, no Desktop required!
What’s Supported?
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Edit existing semantic models - The Power BI service now offers advanced modeling capabilities, including:
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This release enables core modeling features in both Power BI Desktop and the web, allowing you to build and manage models easily from anywhere.
To learn more, refer to the Edit semantic models in the Power BI service documentation, or the Deep Dive into Editing Semantic Models in the Power BI Service (Generally Available) blog post.
This capability allows you to use the familiar Power BI Desktop interface to edit Direct Lake semantic models. All processing occurs in your Fabric workspace, directly against OneLake data, using the Power BI Analysis Services engine instead of your local machine.
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With live edit, every change you make, whether creating new measures, adding calculation groups, defining relationships, running DAX queries, and more, is applied directly to the semantic model in Fabric, ensuring a seamless, scalable modeling experience.
Getting started is easy You can begin in Power BI Desktop or from the web:
Start from Desktop
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Start from the web: In the web experience, select ‘Edit in Desktop’ for the Direct Lake semantic model you have opened. This will launch Power BI Desktop with the semantic model ready for editing.
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To learn more, refer to the Direct Lake in Power BI Desktop documentation, or the blog post.
TMDL view introduces a modern code-first editing experience for Power BI semantic models using the Tabular Model Definition Language (TMDL). A user-oriented modeling language designed to enhance transparency, governance, and efficiency in the development of semantic models. With TMDL view, you can easily make batch updates using simple find-and-replace operations or leverage your preferred generative AI tool to create or modify TMDL code at scale.
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General availability introduces several notable enhancements:
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For more information about TMDL view and full list of capabilities, please refer to our Work with TMDL view in Power BI Desktop (preview) documentation.
A key goal of the TMDL view work was to ensure Power BI Desktop can reliably handle any semantic model configuration. If the model is valid in Analysis Services in a Fabric workspace, it can be opened and edited in Power BI Desktop without crashing. Semantic model metadata not accessible through the user interface - such as multiple table partitions - can still be edited using TMDL view.
Previously, users could use the XMLA endpoint with external tools to make semantic model changes - such as creating multiple partitions - that were supported by Fabric but not by Power BI Desktop. This mismatch often caused Power BI Desktop to crash, which is why downloads were blocked for XMLA altered semantic models. Now that TMDL view is generally available, we’ve removed this limitation. You can now download PBIX files for semantic models modified through the XMLA endpoint, and open and edit them in Power BI Desktop.
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This update does not mean that all semantic models are now downloadable as PBIX files. For example, semantic models with incremental refresh partitions are still not supported for download, this will be addressed in a future update. For more details on PBIX download limitations, please refer to our Limitations when downloading a report .pbix file documentation.
This feature is currently rolling out and may not be fully available in all regions or for all users yet. We appreciate your patience as we complete the deployment over the coming weeks.
To learn more, refer to the Open and edit any semantic model with Power BI tools blog post.
These one-click experiences make it easy to use Fabric Notebooks and Semantic Link to analyze your semantic models directly on the web.
Best Practice Analyzer evaluates models using more than 60 rules across five categories: performance, DAX expressions, error prevention, maintenance, and formatting. It provides guidance on design and performance based on these criteria. Memory Analyzer provides detailed memory and storage statistics for tables, columns, hierarchies, partitions, and relationships, helping you identify optimization opportunities.
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We would like to give a special shoutout to the Power BI community members whose contributions laid the foundation for these tools:
Explore the Power BI Community Notebooks Gallery to discover and share notebooks that enhance data analysis and reporting with the Power BI Community.
Learn more about using notebooks with your Power BI semantic models including details on this feature and its limitations in the Use notebooks with a semantic model documentation.
Semantic models edited in web modeling now have full flexibility of both Direct Lake on OneLake and import table storage modes. Open a semantic model with either Direct Lake tables or import tables and add in additional tables from either storage mode. Choose Get Data to add in import tables from any of the 100s of connectors supported. Choose OneLake catalog and add in Direct Lake tables from any of the Fabric data sources you have access to, including Lakehouses, Warehouses, Mirrored databases, Mirrored Azure Databricks catalogs, and SQL databases in Fabric.
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Once in import storage mode you can transform the table further in Power Query and add in calculated columns to get your reporting where it needs to be. Hierarchies added to import tables also can be used in Analyze in Excel.
To learn more, refer to the Direct Lake overview documentation.
Power BI Desktop can also live edit semantic models with both Direct Lake and import tables.
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Edit relationships, add measures, and adjust column and table properties right in Power BI Desktop.
To learn more, refer to the Direct Lake overview documentation.
Power BI has long supported custom functions in Power Query, however now DAX User Defined Functions (UDFs) provide similar capabilities. DAX UDFs allow you to define custom functions with parameters, just like you would define functions or methods in programming. Instead of copy-pasting chunks of logic across multiple measures, you can now write your logic once and reuse it everywhere.
Complex problems can be encapsulated by multiple reusable functions. Functions can even refer to other functions! This way, your logic becomes easier to write, understand, maintain and debug. Whether you are working on complex models or just want cleaner, more maintainable code, DAX UDFs are for you.
Up to this point, the reusability of DAX logic was limited to calculation groups. DAX UDFs, however, unlike calculation groups, can be parameterized.
Getting started with DAX UDFs
To get started, simply turn on the ‘DAX User Defined Functions’ feature in the preview settings. You can define DAX UDFs in multiple ways, including the DAX Query View and TMDL view.
Defining and using a function
Defining a function is straightforward as we have introduced a new FUNCTION keyword. The general structure for defining a function is:
/// [function description]FUNCTION <FunctionName> = ( [parameter name] : [parameter type] ) => <body>
For example, here is a DAX query that defines and evaluates an extremely simple function that applies a 10% tax to an amount.
DEFINE
/// AddTax returns the amount including tax
FUNCTION AddTax = (amount) =>
amount * 1.1
EVALUATE {
AddTax(11)
} // Return 11
After adding the function to the model, you can then call the function from other places where you can use DAX, such as measures:
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Parameters
Just like built-in functions, DAX UDFs can take zero or more parameters. You can also provide the type of the parameter, so your functions are much more resilient. For example, to identify that our AddTax function expects a numerical value, we could write.
DEFINE
/// AddTax returns the amount including tax
FUNCTION AddTax = (amount: numeric) =>
amount * 1.1
Parameters can not only take scalar values but also accept tables and even expressions.
Type checking
To make DAX and TMDL/TMSL more consistent, we have introduced a set of new functions to do type checking and updated the DATATABLE, CONVERT and EXTERNALMEASURE functions have been updated to work with all synonyms as well. For example, we now have added ISSTRING, which is an alternative to, ISTEXT and ISNUMERIC which is a complement to ISNUMBER.
A complete list is available in our documentation.
Managing DAX UDFs
Functions are shown in the model explorer:
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In DAX Query View, we even added quick queries, so it’s even easier to define and evaluate existing functions or write a brand new one.
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The possibilities are endless
DAX UDFs open a whole new spectrum of options, and this blog cannot do it justice. We encourage you to enable the preview today and try it out for yourself.
Read more in the Power BI DAX User Data Functions documentation. Please let us know what you think. We are looking forward to seeing all the creative uses of UDFs!
When you select ‘Refresh’ in Power BI Desktop, it always performs a schema sync first, followed by a data refresh. While this behavior is convenient in most cases, there are scenarios where you may want to refresh the data without updating the model schema, even if the data source has changed its schema.
For example, in Direct Lake semantic models, the underlying Lakehouse table might have changed (e.g., a new column added). You may want the latest data but prefer not to bring new columns into the model.
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With this month's update, you now have more control over the refresh operation. You can choose to:
These options are also available when you refresh tables individually in the data pane:
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This added flexibility helps you manage your models refresh operations more intentionally, based on your specific needs.
For more information about Power BI Desktop refresh, refer to the Data refresh in Power BI documentation.
In this month's update, when you open a Power BI item which was shared with you in Teams chat or channel, it now opens in separate window—so your chat and other Teams apps stay exactly where you left them.
Previously, opening an item from a Power BI preview card would replace your Teams chat, making multitasking difficult. With this update, items shared in a chat open in a separate window, while your original chat remains visible in a collapsible side panel.
You are now able to access data, maintain ongoing conversations, and utilize additional Teams applications simultaneously.
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Figure - A user selects 'Open' on a Power BI report preview card within a Teams chat. The report launches in a separate Teams window, while the original chat remains accessible in a collapsible side pane.
To learn more about Power BI preview cards in Teams, refer to the Link preview cards in Microsoft Teams chats and channels documentation.
Imagine being able to access your important data just by tapping your device on a small tag. That’s the power of NFC (Near Field Communication) tags. NFC Tag Support is now generally available in the Power BI Mobile app on supported devices!
This feature allows you to register and read Power BI items such as reports, scorecards, dashboards, or even a set of items like an app or workspace on NFC tags directly from the app.
With NFC you can create a seamless connection between your data and the physical world. For example, a retail manager could quickly access inventory data by tapping their phone on an NFC tag placed on a storage shelf. This feature is especially useful for frontline workers who need quick access to data while managing retail floors, inventory, or manufacturing processes.
Getting started is easy: open the Power BI Mobile app, navigate to the item you want to register, press the Register to NFC button in the 3 dots menu, and follow the prompts to link it to an NFC tag. Once you’ve registered your desired item to the tag, anyone with the Power BI Mobile app can get to the item simply by tapping the tag with their device, whether the app is open or not. If the user doesn’t have permission to access the item, they’ll be taken to the request access flow. NFC tags are affordable, flexible, durable, and reliable, and can easily be reused.
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To learn more about NFC support in Power BI mobile, refer to the Connect data to physical locations with NFC tags documentation.
A new tenant setting, all Power BI users can see ‘Set alert’ button to create Fabric Activator alerts, is rolling out this week. This setting will give admins more control over which users can view the Set alert button, which allows users to create Fabric Activator alerts on their visuals, sending real-time notifications based on predefined data conditions.
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When enabled, all Power BI users will see the ‘Set alert’ button in reports. When the setting is turned off, the button will only be visible to users with tenant-level Fabric access, which was the group of users who could see the button prior to this change. Regardless of whether the setting is turned on or off, only users with permission to create Fabric items can set up Fabric Activator alerts.
The benefit of turning this setting on is that it allows users for whom Fabric was enabled for only specific capacities to also set alerts, unlocking the power of real-time alerting for more Power BI users.
This setting is currently disabled and will be turned on by default the week of October 13th.
Advanced Column is easy to use column chart for comparing one or more values with clearly interpretable difference lines. It is best suited for comparison of values between time periods, categories or quantities.
This visual presents the following features:
Try from AppSource.
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The latest update to Zebra BI Tables introduces two powerful features that streamline report building and enhance data storytelling: row calculations from the data model and brand images in rows.
Check out the demo video: Zebra BI May 2025 Update: One Click P&L and Brand Logos in Zebra BI Tables
With the new zero-click reporting functionality, users can now define calculation logic (such as invert, result, skip) directly in the Power BI data model. Simply add a column to your dataset, define the logic with symbols (“=” (Result), “/” (Skip), “-” (Invert)), and with a single drag and drop add it to Zebra BI Tables. The column values will automatically be applied as calculations on the visual, eliminating the need for additional manual setup. It makes the creation of reports like P&Ls, balance sheets, inventory tracking, SaaS metrics, or sales dashboards dramatically faster and more accurate.
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Zebra BI Tables now also supports adding brand images instead of row labels. Especially valuable for consumer goods and retail companies, this feature makes reports more intuitive and engaging. By instantly recognizing brand logos, end users grasp insights faster and spend less time searching for context.
These updates contribute to:
Simplify your reporting with Zebra BI Tables and share your feedback.
The new Word Cloud by Powerviz is available, an advanced visual which empowers you to create some of the most high-quality and creative word art in the Power BI.
Key Features:
Ideal for marketing, education, market research, and presentations—use it for sentiment analysis, SEO keywords, brainstorming, surveys, and engaging communication.
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What makes Drill Down Combo Bar PRO the best custom visual for visualizing categorical data?
It’s all about the drill downs – in Combo Bar PRO, you can create a hierarchy of up to nine category fields, and users can easily drill down by clicking directly on data. Deeper, more focused insights, but only when the user needs them.
The visual is designed to provide top-notch user experience: the slick and intuitive on-chart interactions, the smooth animations, the seamless cross-filtering with other visuals, and full touch support all make Combo Bar PRO a crucial addition to your next report.
And the best part? Combo Bar PRO supports up to 25 series, and each series can be visualized as bars, lines or areas. With a wide variety of customization options, you can create the perfect chart for your use case.
We also recently published a guide on how to create different types of stacked charts with Combo & Combo Bar PRO, including stacked bar, stacked & clustered bar, bar & line, nested bar chart and more.
For a more details, refer to our blog - Power BI Stacked Column Charts: A Full Guide!
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Compare multi-year trends across business units, products, or regions — instantly.
The Compound Annual Growth Rate (CAGR) is a critical metric for visualizing growth trends in financial analysis, strategic planning, and performance comparison.
Now available in Zebra BI Charts for Power BI, CAGR arrows make it easier than ever to communicate multi-year trends directly within your reports. They are especially useful in dashboards that track long-term results, helping users highlight growth patterns and shifts over time.
When used in small multiples, CAGR arrows allow immediate comparison of performance across regions, product lines, or business units — all while maintaining a shared Y-axis for IBCS-compliant reporting.
Each CAGR label includes a color-coded action dot — green for growth, red for negative — with the size scaled to reflect magnitude, offering an intuitive visual cue for trend strength. To simplify reporting even further, Zebra BI Charts automatically calculates the CAGR based on your underlying data.
CAGR provides a smoothed view of performance over time, helping teams refine growth targets, align KPIs, and deliver executive ready insights with clarity and impact.
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To learn more, refer to Introducing CAGR arrows in Zebra BI Charts.
This concludes this month’s update.
We hope the information provided in this update is useful. If you installed Power BI Desktop from the Microsoft Store, please leave us a review.
As always, keep voting on Ideas to help us determine what to build next. We are looking forward to hearing from you!
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