Welcome to the August 2021 update, can you believe that it’s August already?! In this update we have exciting new things for Q&A as well as for Shapes. Also, new this month is Automatic aggregations for DirectQuery. There is more to explore, please continue to read on.

Here is the full list of August 2021 updates:

Reporting

• Customize shape formatting
• X-axis constant line improvements
• Default sensitivity label policy in Power BI desktop  

Analytics

• Sharing Q&A synonyms

Modeling

• New way of expressing Date and DateTime values
• Evaluation configuration settings

Data connectivity and preparation

• One Dataflow Connector (Connector Update)
• Automy Data Analytics (New Connector)
• Azure Databricks (Connector Update)
• Dremio (Connector Update)
• Google BigQuery (Connector Update)
• Quickbase (Connector Update)

Service

• Sensitivity labels for paginated reports
• Leverage automatic aggregations to enhance performance over DirectQuery datasets
• Power BI REST API support for DAX Queries
• Detailed historical activity information for Premium datasets

Mobile

• New mobile report footer

Visualizations

• New Power BI visuals’ store experience
• New visuals
• Timeline by Queryon
• Drill Down Graph PRO by ZoomCharts
• BIpm custom visual by ProcessM
• Editor’s pick

Check out the video below for a summary:

Reporting

 

Customize shape formatting

You can now customize the formatting of the shapes you add to your Power BI reports! We’ve added a number of controls into the Shape card of the formatting pane for a variety of different Shape options, including rounded rectangles, chevrons, arrows, and more. Now you can customize the look of each of the shapes you create, helping you to more flexibly design, structure, and stylize your report pages.

X-axis constant line improvements

Since we introduced the X-axis constant line, we’ve received feedback on ways we can make it an even more useful reference on your Cartesian charts. This month, we’ve acted on that feedback, bringing you conditional formatting for X-axis constant line value and shading for regions before or after the constant line. You can find these new options in the X-axis constant line card in the Analytics pane.

Default sensitivity label policy in Power BI desktop

Security administrations can define a default label to be set on a PBIX file when a user creates a new file or edits an existing file that has no label. Users can change the default label if they see fit. Moving forward, default label policies will be applicable to new content in the Power BI service as well.

Learn more

 

Analytics

 

Sharing Q&A synonyms

Field synonyms are an important part of Q&A because users often have a variety of terms that they use to refer to the same field, such as total sales, net sales, total net sales. This month we’re excited to announce that we now support sharing synonyms for everyone in your organization. This means that you can now leverage your coworkers’ synonyms and minimize duplicate effort when adding synonyms to your models.

How to get shared synonyms

To connect to shared synonyms, navigate to Q&A setup > Field synonyms and click Get more synonyms.

This process may take a few seconds, but once it’s completed, you also have the option to share your synonyms to everyone in your org as well. Note that the synonyms get shared when you publish the report.

Any shared synonyms that match with fields in your model will show up in the Suggested terms section. Then you can click the plus icon (+) on the suggested term to add it a field synonym.

As new synonyms get shared within your organization, you can click the refresh icon to ensure that your Suggested terms are in-sync with your organization:

How to change your sharing synonyms settings

In Power BI Desktop, you can update your sharing synonyms settings in the Q&A setup itself or within the Options dialog under Data Load > Q&A > Share your synonyms with everyone in your org:

You can also update this setting in the Dataset settings within Power BI Service:

Additionally, Admins can choose to disable Synonym sharing within the admin portal by navigating to Tenant settings > Q&A settings:

Modeling

 

New way of expressing Date and DateTime values

We are introducing a new way to express Date and DateTime-typed values as a DAX literal.

This will allow you to directly specify dates and times (up to the second) in you DAX queries, without having to use other functions. Starting with this release, we support either a complete date value or a complete date and time value. The syntax is as follows:

Date format: dt”YYYY-MM-DD”

For example, dt”1999-12-31″ would represent December 31, 1999.

DateTime format: dt”YYYY-MM-DDThh:mm:ss” or dt”YYYY-MM-DD hh:mm:ss”

For example, dt”2021-05-24T12:00:00″ and dt”2021-05-24 12:00:00″  would both represent noon on May 24, 2021.

Note: In the above usages, DAX supports valid date/time components with fewer digits than indicated for ease of use. For instance, January can be specified as either 1 or 01.

As a more practical example, please consider the following. Previously, one might filter their sales to those within a specific order date range by using:

EVALUATE

FILTER (

FactInternetSales,

[OrderDate] > (DATE(2015,1,9) + TIME(2,30,0)) && [OrderDate] < (DATE(2015,12,31) + TIME(11,59,59))

)

However, now you can achieve the same functionality with this more concise syntax:

EVALUATE

FILTER (

FactInternetSales,

[OrderDate] > dt"2015-1-9T02:30:00" && [OrderDate] < dt"2015-12-31T11:59:59"

)

 

Evaluation configuration settings

Power BI Desktop optimizes query performance when importing data or when using DirectQuery by evaluating tables simultaneously. However, in specific situations, you might want to influence the behaviour and change the defaults, for example when the data import is taking too long or Power BI Desktop is taking too much resources on the machine. Until now you could only influence these settings by making changes to the registry. Starting this month, we have added two configuration options to Power BI Desktop:

• Maximum number of simultaneous evaluations. This configures the level of parallelization for query execution in PowerQuery.
• Maximum memory used per simultaneous evaluation. This configures the available memory per evaluation.

Using these settings, you can make sure the loading of data is optimized for your machine, so you get the best experience. Read more.

Data connectivity and preparation

 

One Dataflow Connector (Connector Update)

We are happy to announce an update to Dataflow Connectors in Power BI and the consolidation of the two existing Dataflow connectors into a single Dataflows connector. Dataflow customers will now be able to leverage a single connector to discover, navigate and get data from dataflows created in either Power BI workspaces or Power Apps Environments. In addition, the new connector will provide Power BI Premium dataflow customers with improved performance when authoring dataflows or datasets by leveraging Power BI’s enhanced compute engine. The Dataflows connector can significantly reduce evaluation time for steps performed over computed entities such as performing joins, distinct, filters, and group by operations. There are two specific benefits:

1. Downstream users connecting to this new Dataflows connector in Power BI Desktop can take advantage of better performance in authoring scenarios because the new connector supports query folding.
2. Dataset refresh operations can also fold to the enhanced compute engine, meaning even incremental refresh from a dataset can fold to a dataflow, improving refresh performance and potentially decreasing latency between refresh cycles. Just make sure the compute engine is explicitly set to “On.”

As part of the consolidation into one connector, the Previously named ‘Power Platform Dataflows’ connector will be renamed to ‘Dataflows’ connector and the ‘Power BI Dataflows’ connector will be renamed to ‘Power BI Dataflows (Legacy)’ connector and will eventually be removed from the ‘Get Data’ menu.

All existing Dataflows and Datasets created using either connector will continue to function without interruption, will not be impacted by the name changes, and no action is required to maintain their long-term functioning. When creating new Datasets from Dataflows, we recommend choosing the ‘Dataflows’ connector in ‘Get Data’ in Power BI Desktop under the ‘Power Platform’ category. If you have existing datasets connected to Dataflows, consider trying out the new connector to take advantage of the improvements in this initial release.

Lastly, thank you for this idea. Continue to vote for new ideas and tell us how to better serve you. We take your ideas seriously!

Automy Data Analytics (New Connector)

We are excited to announce the release of the Automy Data Analytics connector, by ACEROYALTY! Here are some notes from the ACEROYALTY team.

We are happy to announce the new Automy Get Data connector this month!

Extend the reporting capabilities of Automy and capture it within your Power BI architecture to quickly share across your organization. Automy provides integrated software and data solutions for process automation. The Automy connector for Power BI brings a whole new experience to analytics. Our market-leading process automation capabilities enable you to combine multiple data from workflows and processes, into a single virtual data layer on-demand without copying or moving data. All your automation data in Power BI without any manual work. Reduce time & increase accuracy when getting data, adding calculated columns and other query edits, and pulling in the data from custom fields, are just a few capabilities that Automy connector brings.

This connector can be found in the Online Services category of the Get Data dialog.

Azure Databricks (Connector Update)

The optional flag “Fast Evaluation” improves refresh performance of DirectQuery reports and imports. This is available for Databricks SQL and for Databricks Runtime versions starting at 8.3 and later.

Dremio (Connector Update)

The connector has been updated to Version 1.0.7. Here is the set of updates from the Dremio team.

Add support for connecting to Dremio Cloud. The Dremio Cloud connector shows up as a separate connector along with the previous connector for software now renamed as Dremio Software. The methods of authentication available for Dremio Cloud are Azure Active Directory and Personal Access Token. Method of authentication for Dremio Software is unchanged.

Google BigQuery (Connector Update)

We are excited to announce support for native database queries for the Google BigQuery connector.

Similar to SQL and Snowflake connectors, this will allow you to input a Google BigQuery native query and build reports on top of it. In this initial version, you will need to specify a Project ID and use fully qualified table names of the format ProjectID.Schema.Table.

For example: SELECT * FROM ProjectID.Schema.Table.

We are working on improving this experience in upcoming updates.

Quickbase (Connector Update)

We are introducing a new version of the Quickbase connector. Firstly, the logo and company name has been updated to new brand identity.

Also, the new connector will use the more modern RESTful API, which you can read more about here. Briefly, this API has been designed from the ground up to ensure that we provide a consistent experience, with capabilities that we will continue to expand on and invest in for years to come. As a result of the upgrade, we have been able to implement several backend performance improvements and bug fixes. Functionally, we have been able to add support for Custom Fields that are defined in reports. As new capabilities are added to the RESTful API we will continue pass through those benefits to the connector.

Service

 

Sensitivity labels for paginated reports

Now you can set MIP sensitivity labels on paginated reports in the Power BI service, just like you can on Power BI reports. When data from a paginated report is exported to a Word, Excel, PowerPoint, or PDF file, the report’s label and protection settings be applied to the exported file.

Learn more

Leverage automatic aggregations to enhance performance over DirectQuery datasets

Automatic aggregations enhance performance over DirectQuery datasets by automatically creating aggregations, based on the users’ historic query patterns. Using machine learning, automatic aggregations determine, creates, and maintains the most optimal set of aggregations for the users’ workload. Users no longer need to have extensive data-modeling or advanced query optimization experience and can leverage the power of this feature with just a few clicks.

Power BI REST API support for DAX Queries

We are very excited to announce the preview of a new REST API to query datasets in Power BI by using Data Analysis Expressions (DAX). Among other things, this new DAX REST API helps to address customer feedback concerning programmatic access to the data in a dataset (for example, the idea REST API access to READ datasets with almost 500 votes by the time of this announcement). The new DAX REST API avoids dependencies on Analysis Services client libraries, requires no connection to XMLA endpoints, and works in Power BI Premium as well as in Power BI shared capacity. In short, there are many good reasons for BI solution developers to evaluate this REST API during the preview period.

One of the greatest advantages of a REST API to query datasets is that you can use this REST API in practically any modern development environment on any platform, including low-code no-code Power Apps, Power Automate, and Logic Apps, JavaScript-based languages, PowerShell, Java, PHP, Ruby, Python, or any other technology that can authenticate against Azure Active Directory (AAD) and construct a Web request. Of course, you can also use .NET to call this REST API. As other Power BI REST APIs the DAX REST API supports user accounts, service principals, and works in B2B scenarios, and because the caller is fully identifiable, row-level security and other controls at the dataset level are applied as expected – with the caveat that RLS is not supported for service principals. See the limitations section in the Row-level security (RLS) with Power BI product documentation.

Yet, before you take this new REST API for a test spin, note that the tenant-level setting Allow XMLA endpoints and Analyze in Excel with on-premises datasets must be enabled in the Power BI admin portal, as depicted in the screenshot below. This setting is enabled by default, but double-check with your Power BI admin. At least for the duration of the preview period, it seemed appropriate to govern this new DAX REST API with the existing XMLA endpoints tenant setting, The DAX query functionality is comparable to XMLA read access. We are still evaluating if this DAX REST API should have its own tenant setting. Please give us feedback if you want to influence this decision.

 

Equally important and consistent with XMLA read access, you need the Build permission for the dataset you want to query by using this new REST API. Contributors and workspace admins have this permission, but you can also grant it directly, as in the following screenshot. For more information, see Build permission for shared datasets. Also note that the workspace must be a modern (v2) workspace. Classic (legacy) workspaces are not supported. So, if your datasets still reside in a classic workspace, make sure you upgrade the workspace to the new (v2) workspace experience.

Perhaps the easiest way to test the DAX REST API is to query a dataset by using the Power BI Management cmdlets. See the following screenshot for a straightforward sample script based on an AdventureWorks dataset.

Essentially, the above script performs the following main steps:

1. Construct the request parameters. This includes the request URL and the request body.
2. The request URL references executeQueries endpoint of the dataset you want to query. The dataset Id identifies the dataset. There are many ways to determine the dataset id. Perhaps the easiest is to display the dataset settings in the browser and then copy the dataset Id from the URL in the address bar.
   The URL has the format: https://api.powerbi.com/v1.0/myorg/datasets/{datasetId}/executeQueries. If you use the Power BI Management cmdlets, you also can work with relative URLs, as in the script above.
3. The request body is a JSON document containing the DAX query you want to run and an optional parameter to specify if blanks should be returned as null values or not. The default omits blanks which helps to reduce the data volume. More importantly, note that the request body consists of a queries array, but currently you can only specify a single query. The queries array provides flexibility for future improvements, but currently it can only contain a single query item. Here’s a template for the request body. Replace ‘<Your DAX Query>’ with your actual DAX expression and don’t forget to escape quotation marks with a backslash (\”).
   { “queries”: [{“query”:”<Your DAX Query>“}], “serializerSettings”:{“incudeNulls”: true}}
4. Send the request to Power BI. The DAX REST API expects a POST request, which you can construct in PowerShell by using the Invoke-PowerBIRestMethod cmdlet. Don’t forget to login to Power BI and then specify Post as the Method and pass the request URL and request body as demonstrated above and the job is done. The Power BI Management cmdlets have the required app permissions to use the DAX REST API.
   If you want to use your own app registration, make sure your app has the Dataset.Read.All or Dataset.ReadWrite.All permission. For details about registering an app with Power BI, see Register an Azure AD application to use with Power BI in the product documentation.
5. Parse the JSON response and process the results. The DAX REST API returns a JSON document with a results array containing one result per input query. Because the API currently only supports a single DAX query, the results array will also only include a single item. This item might include one or multiple tables depending on what the DAX query returns, which in turn contain the rows with the actual results as key/value pairs with the keys referring to the column names. In the script above, the line $parsed.results[0].tables[0].rows | Format-List outputs the rows of the first (and only) table of the first (and only) result item returned for the (one and only) DAX query.

A .NET implementation that produces the same results as the PowerShell script above is equally uncomplicated. See the following screenshot with a code snippet and the resulting sample output. You can download this code sample at https://github.com/microsoft/Analysis-Services.

As mentioned already, remember that the request body currently can only contain 1 DAX query and accordingly there is only 1 result set. Future versions of the API might support more. Also note that the result set is currently capped at 100k rows. If you need to retrieve more rows, you must construct and submit multiple DAX queries that each only retrieves an appropriate portion of the results. Moreover, the result set does not support binary data. Make sure your values are of the type string, numeric, boolean, blank, date time or variant. Needless to say, that this is a Power BI API and therefore not available in Azure Analysis Services or SQL Server Analysis Services. And because this is a DAX REST API, you cannot submit MDX queries.

While it is certainly not complicated to construct a Web request manually, we are also aiming at adding the DAX REST API to the Power BI .NET SDK and the Power BI Connector for Power Automate, Power Apps, and Logic Apps so that it is even easier for you to leverage the data from your Power BI datasets in your business solutions. For example, you could then query certain key performance indicators in Power Automate and trigger appropriate subprocesses based on the results. So, stay tuned, but don’t delay and try out this new REST API today! Let us know of any additional requirements you might have through the usual Power BI community channels or as comments to this article below. And thank you very much for any feedback you’d like to share with us during this preview phase.

Detailed historical activity information for Premium datasets

Workspace administrators can now enable collection of Power BI user activities and metrics for any Premium workspaces they own. This preview capability provides near real-time information reported by the Analysis Services engine about dataset activity. This allows you to monitor load, observe usage trends, spot periods of unusual activity, and identify performance degradation with queries or dataset refresh operations. We have partnered with Azure Log Analytics to allow you to send your Power BI activity data to your own Azure environment. This gives you up to 2 years of data retention with ad-hoc query and alerting.

The Power BI Service administrator can enable this capability for Workspaces in Tenant Settings:

 

A workspace administrator can then set up logging within Workspace Settings. The example below shows a completed configuration:

 

We have published a template report to allow you to get insights on your activity data right away, without having to understand how to parse and transform the log data. The example below shows the Query Statistics page which can be used to identify queries with inconsistent performance:

To learn more, please check out the announcement and documentation.

Mobile

 

New mobile report footer

We’ve updated the report footer to make it easier to find and understand all the actions you can do with reports.

Visualizations

 

New Power BI visuals’ store experience

Power BI visuals’ embedded store is getting a new look where you can browse all visuals allowed in your organization.

Read more about the new experience here.

New visuals

New visuals this month are:

• Floor Plan Visual by Simpson Associates
• Timeline Box by TheraTraq
• Timeline Basic by TheraTraq
• Phrazor by vPhrase Analytics Solutions Pvt. Ltd
• Balance Sheet Visual by K Team Solutions GmbH

 

Timeline by Queryon

Timeline by Queryon makes the single-Axis timeline as beautiful and flexible as possible and provides your users with impactful visuals enabling intelligent decisions.

Use Timeline to visualize project milestones, key events, and project finish times. Mark important dates such as holidays and birthdays and share your downloadable iCalendar with the staff. Create your timelines using various styles include line, bar, waterfall, and kaban style layouts. For a more detailed description check out  https://queryon.com/timeline/

Here is the link to the video.

Drill Down Graph PRO by ZoomCharts

Build networks and explore relations within them with the first true graph visual for Power BI.

The first and only visual within Power BI that allows you to visualize graph data! Map and explore relations among data points, identify outliers and discover patterns. On top of it you will enjoy ZoomCharts unrivaled data visualization experience with advanced customization capabilities, cross-chart filtering, and smooth drilldowns.

This visual offers in-app purchases and comes with 30 days free access to the paid features.

Main Features:

• Automated graph structure – add data and visual will be constructed automatically
• Force feedback layout – examine data points effortlessly with the layout preventing node overlap
• Node selection – “left click” for single data point, “ctrl+click” and “rectangular selection” for grouping
• Bi-directional links – visualize relations using “from” and “to” to demonstrate the flow of data
• Multiple links – separate incoming and outgoing values for each of the data points
• Rich customization options – customize nodes labels, links, link decorations, add images
• Cross-chart filtering –select data points on multiple charts instead of using slicers
• Multi-touch device friendly – get equal experience on any device

Create reports and Power BI graphs that are easy to use. To evaluate Drill Down Graph PRO for free, start your 30-day trial period here.

Link: Our Power BI Graph PRO Chart.

BIpm custom visual by ProcessM

In addition to many helpful available visuals in Power BI, ProcessM introduced BIpm custom visual. It’s an independent visual doing process mining to investigate real behaviors over your process data to accomplish the organizational data analytical mission. ProcessM introduced BIpm custom visual as the simple, interactive, agile, and user-friendly solution to study process models over multidimensional event logs in Power BI, thereby having a reliable platform for comprehensive enterprise mining. Furthermore, doing process mining analysis inside Power BI supports the “process cube” idea introduced in the academy beforehand. Consequently, it yields managers and decision-makers to comprehensively translate discovered insights to gain improved decisions and better performance more quickly.

As an example of many practical analytical tasks by BIpm, you can compare the various process models of the input data’s multi aspects by setting the different filters. For instance, the following figure shows the processes for gold and silver customers separately.

Do not hesitate to start process mining now on your process data (event log) by visiting AppSource and downloading BIpm.

Questions or remarks? Check our website: https://processm.com/

See other samples for process mining dashboards: https://processm.com/bipm-pro/demo-dashboards/

Editor’s pick

The Editor’s picks visuals of the month are:

• Drill Down Map PRO by ZoomCharts
• Craydec Timelines
• KPI Ticker by MAQ Software
• Collage by CloudScope

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 over 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!