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Welcome to the November 2023 update. We’ve got a lot of great features this month including DAX Query view, Semantic Model Scale-out, and Advanced Filtering for Paginated Reports.
There is more to explore, please continue to read on.
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With so many upgrades and enhancements in the new Button slicer, we continue to go beyond the improvements you saw in the new card visual, and the following list of features will have you on the edge of your seat, so let’s have a look!
With this preview update, the new Button Slicer feature has been toggled ON by default for your convenience and is found in either the Visual gallery on the ribbon, or by selecting Build a visual after right-clicking on the canvas, and then choosing the new slicer, or lastly, by selecting new slicer from the on-object dialog. You can also toggle this feature preview ON or OFF by looking under Options > Preview features > New button slicer.
What’s next?
Remember, this was only the first stage on the new slicer roadmap. So, fasten your seatbelt, and get ready for the exciting journey ahead as our next stage unfolds and reveals even more Power BI updates, enhancements, and features! Coming next, the List and dropdown slicer!
If you’re looking to learn more about the New button slicer, watch out for a dedicated blog post in the coming days. If you don’t want to miss it, make sure to subscribe to the Power BI blog or follow Power BI Visuals on LinkedIn.
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With Reference labels offering an abundance of creative possibilities, you and your users will be astounded by the world of wonder they unlock. Here's an overview of the available features!
With this preview update, the new Reference Labels feature has been toggled ON by default for your convenience and is found in either the Visual gallery on the ribbon, or by selecting Build a visual after right-clicking on the canvas, and then choosing the new slicer, or lastly, by selecting new slicer from the on-object dialog. You can also toggle this feature preview ON or OFF by looking under Options > Preview features > Reference labels.
What’s next?
With the first and second stage of the new Card visual now delivered, you can imagine what exciting features are waiting for you as we continue this journey together.
If you’re looking to learn more about reference labels in the new card, watch out for a dedicated blog post in the coming days. If you don’t want to miss it, make sure to subscribe to the Power BI blog or follow Power BI Visuals on LinkedIn.
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Today, the Q&A visual doesn't rely on generative AI to function. The Q&A engine processes your natural language input all inside Power BI algorithmically using a variety of linguistic principles, associating words and phrases you use with data in your model. This makes it good at answering precise questions about your data, but it may not be able to associate everything you input with data in the model. To help authors ensure that the Q&A visual provides consistent and accurate answers based on the unique language their report consumers actually use, we introduced Q&A setup tools with an emphasis on providing Q&A with synonyms for column and table names in the model. This way, authors can explicitly define different ways people might refer to their data, and users will always receive the correct answers when they ask similar questions in the future.
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Power BI recognizes two types of synonyms: approved synonyms and suggestions. Approved synonyms either come directly from the names of fields themselves or are explicitly added by the author. When you uses an approved synonym in your Q&A input, it will be treated just as though you used the name of the field and the association will be presented with high confidence, signified by a solid blue underline.
Suggested terms are words Power BI thinks are likely to refer to their corresponding name. They come from a variety of sources – synonyms from the Office thesaurus show up by default, but you can also connect to your organization's collection of approved terms and add those to your suggestions as well. Suggestions will still be used by Q&A, but with lower priority than approved synonyms, and the lower confidence will be signaled in the results with a dotted orange underline. In the Q&A setup menu, suggestions can be added to the approved synonyms list or removed entirely.
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Managing synonyms is therefore an important part of improving the quality of the Q&A experience. However, coming up with synonyms for every data entity in your model can be mentally laborious and physically time-consuming. Copilot for Power BI streamlines this process by generating some for you!
If you have Copilot enabled, there are a few ways for you to get suggestions from Copilot. But first, you'll have to enable the feature in Power BI Desktop in File > Options > Preview features > Improve Q&A with Copilot.
Then, you might be prompted to add synonyms with Copilot via a banner that shows up the first time you make a Q&A visual or open the Q&A setup menu:
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You'll also be able to get Copilot suggested synonyms via the Q&A setup menu. You can turn on Copilot as a source in the suggestion settings menu in the synonyms tab, then hit apply to get synonyms. Or, if Copilot is already enabled as a source, you can click the refresh button next to the suggestion settings dropdown.
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After you've gotten these suggestions, you might be prompted to review them. You'll find the new synonyms in the suggestions column in the synonyms page of the Q&A setup menu:
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Copilot-suggested synonyms will function just like any other suggested synonyms. This means that they may be used by Q&A as a fallback when trying to determine what data fields a natural language input may refer to. Carefully review them in the suggestions column of the Q&A visual, remove the synonyms which are inaccurate, and approve the ones which best fit the data.
Keep in mind that as we scale out Copilot, you might run into throttling, which may cause Copilot to return incomplete results if you send too many requests in a short period of time. If that happens, you can wait a bit and try again. Copilot may also not return results for terms for which it cannot generate synonyms, or when its results are deemed inappropriate by our content filter.
Like we mentioned in our release of linguistic relationships for Q&A, we see our investment into both Copilot and the Q&A visual as mutually beneficial. There will be more features coming soon, so keep an eye out for the new ways in which we're bringing the two together!
Most requested, this month we are bringing you the ability to configure your pane switcher to stack panes instead of swap. If you preferred the behavior from before where panes opened side-by-side by default, you can now configure this setting by checking the new option for “always open in new pane” from either the Options menu or the View ribbon.
To achieve the stacked behavior of panes as before:
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Turn on the new option within the Options menu:
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Or, select the new option from the View ribbon:
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Resizing the data flyout:
Also highly requested, this month we’ve also added the ability to resize the data flyout (second flyout) from the build button when working with long field names.
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Note we have a known bug: there may be cases where the resize handles appears to the left of the data flyout if there is not enough space to expand on the right side. We're working on a fix! As a workaround in these cases, you can move the visual to left temporarily on the canvas to resize the data flyout.
Table’s add button is back!
Table has the add button again! Originally, we had to remove the add button from the Table visual type as currently the only chart element to add from this menu was the title that does not have a default value. This added confusion to the experience because simply turning on the title did not appear to have changed anything in the visual, and users had to go to the format pane to type in their visual title. Last month we shipped placeholder text which allowed us to bring back the add button for Tables. Now, when turning on title, a placeholder will appear to type directly onto the visual.
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New on-object default setup coming soon!
Each month we’ve been working toward giving users more flexibility for how they prefer to work with the PBI editor. With this month’s addition of the new “always open in new pane” setting, next month we’ll be able to introduce a new default setup that feels closer to the previous classic look. With this new default, we help you preset the following options with just 1 click!
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With this release, Azure Maps now aggregates points with the same latitude and longitude values in the same way that it does with location names, allowing you to see them as one bubble. These aggregated points can then be filtered or grouped as you would normally.
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Users have the ability to choose whether they want to summarize over the entire report, select pages, or even specific visuals across their report, giving them flexibility in what their summary looks like. Users will also see references for each portion of the summary that align to visuals on the various pages on the report, from which the summary lines were generated, making it easy to validate the summary’s accuracy and tie it back to the data.
The summary can be updated as the data is sliced and diced, so end users can interact with it, without editing the prompts themselves.
The narrative visual with Copilot makes it faster to communicate insights about the data that matters to you. The visual is available in the service and in Power BI Desktop.
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This powerful way to interact with your data model is now available in the new DAX query view. We give you several ways to be as productive as possible.
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Mark as date table
Within the Service, you can now mark a table in your data model as a date table. Marking a date table in your model allows you to use this table for various date-related elements including visuals, tables, quick measures, and more, with full Time Intelligence support. To set a date table in the Service, right-click on the desired table and choose ‘Mark as date table > Mark as date table’ in the menu that appears.
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Next, specify the date column by selecting it from the dropdown menu within the 'Mark as date table' dialog. Power BI will then perform validations on the selected column and its data to ensure it adheres to the 'date' data type and contains only unique values.
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Rename and delete tables and columns
Within the Service the following functionality is now supported:
Data Connectivity
Empower your data insights with our cutting-edge Power BI data connector for Azure Resource Graph! Now, seamlessly transform your Azure Resource Graph queries into stunning visualizations within Power BI. Elevate your analytics game and make data-driven decisions with ease. Unlock the synergy of Azure Resource Graph and Power BI today!
Profisee's Power BI Connector Version 3.0 exposes new information around data quality, enhancing analytics on data quality improvements for data managed in Profisee with detailed information regarding validation issues flagged within their data. Additionally, the data types have been refined streamlining the experience for users using the Profisee Connector to load data from Profisee to Microsoft Fabric using Data Factory Gen 2 Data Flows.
This version of the Bloomberg Data and Analytics connector for Power BI includes changes to support underlying infrastructure updates and back-end performance enhancements. All user-facing features remain unchanged.
Introducing the public preview of the new Explore feature, where users have a lightweight and focused experience to explore their data. Similar to exporting and building a PivotTable in Excel, now, directly within Power BI users can quickly launch Explore to begin creating a matrix/visual pair to get the answers they need without all the distractions and extra complexity of reports.
Simply find a dataset or report you’d like to explore:
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Begin building your matrix/visual pair to get to the answers you need:
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And, if you’d like to return to your work save it as an exploration:
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Find more details in the Introducing Explore (Public Preview) blog post coming soon.
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Head over to our Ignite blog Empower Power BI Users with Microsoft Fabric and Copilot to read all the announcements related to Copilot. We’ll share more details in a dedicated blog next week.
Check out the Copilot for Power BI Docs for complete instructions and requirements and don't hesitate to leave a comment in the Fabric Community site if you have any questions.
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OneLake integration can even help you if you don’t plan to query the data. Perhaps you only want to export the data to backup files. Thanks to OneLake integration, this is very straightforward now. Ensure that your import-mode semantic model is hosted in a workspace on a Premium or Fabric capacity and that the large dataset storage format is enabled. Then, enable OneLake integration and perform a manual or scheduled data refresh operation. That’s it! The semantic model writes the imported data to the delta tables as part of the refresh operation. Exporting import-mode tables has never been easier. The delta tables are kept up to date without requiring any ETL pipelines copying data.
Of course, you can also export the data programmatically via Tabular Object Model (TOM) and Tabular Model Scripting Language (TMSL) if you can access your semantic model through XMLA in read-write mode. For example, you can open SQL Server Management Studio (SSMS) and run the following TMSL command (see also the screenshot below):
{
"export": {
"layout": "delta",
"type": "full",
"objects": [
{
"database": "<Name of your database>"
}
]
}
}If you have installed the latest version of OneLake File Explorer, you can conveniently verify the success of the export process by using Windows File Explorer. In OneLake File Explorer, right click on the workspace folder and select Sync from OneLake. Then, in the workspace folder, look for a subfolder with a name that matches your semantic model and that ends with .SemanticModel, as in the screenshot above. In this semantic model folder, every import-mode table has a subfolder that contains the delta table’s parquet files and delta log.
But you don’t need to know these file system details if you add shortcuts for your semantic model’s delta tables to other workloads in Fabric, such as lakehouses etc. Simply launch the Shortcut Wizard UI, pick Microsoft OneLake, select the semantic model, and then pick the tables you want to include, as in the screenshots below, and that’s it. You are ready to read and query the tables using your favorite data tools and APIs.
And there you have it! Now you can use Direct Lake mode to read delta tables directly from OneLake and write delta tables thanks to OneLake integration. Fabric is redefining how customers can build their BI solutions for faster performance at big-data scale while at the same time reducing Total Cost of Ownership (TCO) and infrastructure complexity. For example, you no longer need an entire portfolio of homegrown ETL solutions to get data volumes of any size in and out of semantic models. So, don’t delay and see for yourself how OneLake integration can help you maximize the return of your investments into semantic models by making the data instantaneously and concurrently accessible to data scientists, DBAs, app developers, data engineers, citizen developers and any other type of data consumer you may have in our organizations through delta tables added to your Lakehouses and Synapse Data Warehouses via shortcuts. And as always, provide us with feedback if you want to help deliver additional enhancements. We hope you are as excited about OneLake integration as we are. We think this is a massive innovation and are looking forward to hearing from you!
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There is (almost) nothing special for RLS/OLS in Direct Lake models. You can define roles and assign users as for any other semantic model type. But keep in mind that by default Direct Lake models use single sign-on (SSO) authentication to the underlying data source. Using RLS/OLS in conjunction with SSO can be challenging because it involves multiple authorization layers—RLS/OLS in the semantic model and user authorization at the data source. For example, if you wanted to authorize a new user, you would have to add that new user to appropriate RLS roles and ensure that the user has access permissions to the underlying delta tables in the lakehouse or data warehouse.
Managing user authorization at multiple layers adds complexity and friction. That's why we are excited to introduce support for stored credentials with Direct Lake semantic models. Your semantic models can now access the delta tables at the source with a single, fixed identity on behalf of the users instead of delegating the actual user identities via SSO. When adding new users to an RLS role, you are effectively authorizing them to use the fixed identity. Because this approach avoids SSO-related complexity and friction, we strongly recommend that you switch to a fixed identity whenever you add RLS/OLS to a Direct Lake model. Switching to a fixed identity is as easy as binding the Direct Lake model to a Shareable Cloud Connection (SCC) that has SSO disabled. For more information, see Connect to cloud data sources in the Power BI service in the product documentation.
Here are the steps to configure a Direct Lake model with a fixed identity:
The ability to set up stored credentials is available today! The RLS editor for Direct Lake datasets in the web modeling experience is being deployed and will be visible in the coming days or weeks.
And that’s it for this announcement of RLS/OLS with fixed identities for Direct Lake semantic models. For more information see the articles about Direct Lake semantic models in the product documentation. We hope that these exciting new capabilities enable you to create and migrate even more Power BI semantic models to Direct Lake mode so that you can take full advantage of all the data movement, data science, real-time analytics, and Office integration, and AI, and BI capabilities that Fabric and Power BI have to offer. And please provide us with feedback if you want to help shape the future on world’s best and most successful BI service – Power BI on the unified Fabric platform! We always love to hear from you!
Learn about Direct Lake in Power BI and Microsoft Fabric - Power BI | Microsoft Learn
Here's a quick summary of the benefits semantic model scale-out can provide to your reports, dashboards, and other BI solutions:
Please refer to the Configure dataset scale-out article in the product documentation for details on how to enable semantic model scale-out.
This new view mode is similar to how Show as a table displays underlying data for individual visuals today. Show visuals as tables will display the underlying data for visuals for all pages in the current report, with the added functionality of interaction and cross-filtering capabilities.
To activate this view mode, navigate to the view dropdown menu and select Show visuals as tables.
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To revert, select Show original visuals.
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Or simply use the keyboard shortcut Control + Shift + F11 to toggle between the two views.
Learn more details about this feature, including limitations, in our documentation: Consuming reports in Power BI with accessibility tools
Watch the video of the new functionality!
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With this feature, you can now display multiple text columns in a tabular way, which leads to a better understanding of the data when displaying more attributes of the same Category. Additionally, there is no need to apply any complex DAX functions. Simply add additional text columns into the ‘Values’ placeholder.
SOME POPULAR USE CASES:
In one-to-one mapping, you usually need to add additional information next to the descriptive column to ensure data accuracy, consistency, and ease of reference.
Try it on your data today for free.
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Key Features:
Business Use Cases:
Check out the visual features in the demo file.
Step by Step instructions and documentation.
To learn more, visit the Powerviz website.
Funnel Chart by Powerviz Feature Video on YouTube.
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Main features include:
ZoomCharts Drill Down Visuals are known for their interactive drilldowns, smooth animations, rich customization options and support: interactions, selections, custom and native tooltips, filtering, bookmarks, and context menu.
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Other
In this challenge, you will learn how to connect to data, ingest it with Data Factory and notebooks, store it in the lakehouse or data warehouse, and create Power BI reports to turn your data into competitive advantage.
The challenge will help you prepare for the Microsoft Certified: Fabric Analytics Engineer Associate certification and new Microsoft Applied Skills credentials covering the lakehouse and data warehouse scenarios, which are coming in the next months.
You can also bind datasets dynamically to a paginated report visual as outlined in the “Bind datasets dynamically to a paginated report visual” documentation.
That is all for this month! Please continue sending us your feedback and do not forget to vote for other features that you would like to see in Power BI! We hope that you enjoy the update! If you installed Power BI Desktop from the Microsoft Store, please leave us a review.
Also, don’t forget to vote on your favorite feature this month on our community website.
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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