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Category: Power BI

Tracking High-Level Power BI Import Throughput Stats

Chris Webb collects some measurements:

In the first post in this series I described the events in Log Analytics that can be used to understand throughput – the speed that Power BI can read from your dataset when importing data from it – during refresh. While the individual events are easy to understand when you look at a simple example they don’t make it easy to analyse the data in the real world, so here’s a KQL query that takes all the data from all these events and gives you one row per partition per refresh:

Click through for the KQL script, as well as what it all means and what you can get out of it.

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Power BI: Git Integration vs Deployment Pipelines

Marc Lelijveld notes a chemical reaction:

Together with the introduction of Microsoft Fabric a long-awaited feature for Power BI also became available. Git integration now allows us to connect your workspace to a git repository to sync the meta data from your Power BI dataset and report between the workspace and the repository.

At the same time, Power BI deployment pipelines are around. The pipelines help you to move content between workspaces from Development to Test and finally to Production. The question that arises, when to use what? And how do they complement each other, or maybe even clash with each other?

Read on for Marc’s thoughts across these two topics.

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Creating a Power BI Deployment Pipeline

Richard Swinbank does some deployment:

In part 4 of this series, I introduced a standard pattern for organising report files and pipelines, with a standard process for creating new reports. Repeatable patterns and processes are great candidates for automation, and in this post I’ll build a report creation process that automatically configures a new report and creates its deployment pipeline .

This video (5m31s) shows you the process in action, from creating a new report to seeing it deployed automatically to Power BI:

Click through for the video, as well as plenty of written instruction.

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Viewing the Power BI Format Pane during On-Object Interaction

Gilbert Quevauvilliers is missing something:

I have enabled the new On-Object Interaction for the formatting pane in Power BI and while it is constantly improving there are times when I would like to have the good old formatting pane available.

I have also found that sometimes when you create a new visual there is no option to format it as shown below.

There’s a workaround to this, so check it out.

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Taking Over a Power BI Dataset with a Service Principal

Angela Henry takes it out of the user’s hands:

A little background for those new to using Power BI and Data Gateways. If the data source for your Power BI dataset lives on-prem or behind a private endpoint, you will need a Data Gateway to access the data. If you want to keep your data fresh (either using Direct Query or Import mode), but don’t want to rely on a specific user’s credentials (because we all want to go on vacation at some point), you will need to use a service principal for authentication.

Read on for the step-by-step instructions on how to do this.

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Filtering Calculation Items in a Slicer

Marco Russo and Alberto Ferrari do some slicing and filtering:

Slicers with too many values might be inconvenient for users, as they must search for the desired selection among too many lines. In such cases, a common solution is to build a hierarchy and use slicers with multiple columns inside, or multiple slicers, each with one column. However, this solution works only in structures with a natural hierarchy, like continents and countries. Indeed, each country belongs to only one continent so the hierarchy can be easily created with a new column.

If the hierarchy is non-natural, the relationship between the parent and the children is many-to-many, requiring a specific type of relationship. 

Click through to see what that relationship looks like and how you can build it.

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An Overview of Semantic Modeling in Microsoft Fabric

Teo Lachev talks semantic modeling:

In retrospect, I’d say I owe 50% of my BI career to Analysis Services and its flavors: Multidimensional, Tabular, and later Power BI. This is why I closely follow how this technology evolves. Fast forwarding to Fabric, there are no dramatic changes. Unlike the other two Fabric Engines (Lakehouse and Warehouse), Power BI datasets haven’t embraced the delta lake file format to store its data yet. The most significant change is the introduction of a new Direct Lake data access mode alongside the existing Import and DirectQuery.

Read on for Teo’s thoughts. I think there’s a good chance that the Bad/Ugly points will be eliminated by the time Fabric goes GA, though we’ll have to wait and see if that’s the case.

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Power BI Treemap Visual Desired Enhancements

Meagan Longoria has an airing of grievances:

I recently created a treemap in Power BI for a Workout Wednesday challenge. Originally, I had set out to make a different treemap, but I ran into some limitations with the visual. I ended up with the treemap below, which isn’t bad, but it made me realize that the treemap is in need of some improvements to make it really useful. So I decided to share my thoughts here.

Read on for Meagan’s thoughts on the existing treemap visual. I agree with all of Meagan’s points and would love to see this visual be updated.

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Analyzing Power BI Refresh Performance with Log Analytics

Chris Webb starts a new series:

If you’re tuning refresh for a Power BI Import mode dataset one of the areas you’ll be most interested in is throughput, that is to say how quickly Power BI can read data from the data source. It can be affected by a number of different factors: how quickly the data source can return data; network latency; the efficiency of the connector you’re using; any transformations in Power Query; the number of columns in the data and their data types; the amount of other objects in the same Power BI dataset being refreshed in parallel; and so on. How do you know if any or all of these factors is a problem for you? It’s a subject that has always interested me and now that Log Analytics for Power BI datasets is GA we have a powerful tool to analyse the data, so I thought I’d do some testing and write up my findings in a series of blog posts.

In the first post, Chris gives us an overview of information available and provides one way to query it.

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Power BI Report Deployment with Connections to Shared Datasets

Rayis Imayev does some large-scale deployment:

Let’s say you have a collection of Power BI .pbix files stored in a git-based source control system (GitHub, Azure DevOps, or any other system). Among these files, one is your data model, while the others are Power BI visual reports and dashboards connected to the published dataset from your data model. Your published dataset is located in a separate workspace dedicated to shared content, and the visualization Power BI reports are placed in another workspace with appropriate permissions to access them.

Now, let’s consider an additional complexity: you have this collection of files not only in one development environment but also in two others. These environments support your Power BI reporting testing (UAT) and the release of your Power BI reports to end-users (Production).

The questions that arise are: How do you deploy your solution, and most importantly, how do you automate it?

Click through for an architectural diagram, as well as the answer to this question.

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