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Category: Power BI

Using Semantic Model Scale Out as Part of Power BI Refresh

Published 2024-07-30 by Kevin Feasel

Chris Webb keeps the lights on during a refresh:

In recent my posts on the Command Memory Limit error and the partialBatch mode for Power BI semantic model refresh, I mentioned that one way to avoid memory errors when refreshing large semantic models was to run use refresh type clearValues followed by a full refresh – but that the downside of doing this was that your model would not be queryable until the full refresh had completed. Immediately afterwards some of my colleagues (thank you Alex and Akshai) pointed out that there was in fact a way to ensure a model remained queryable while using this technique: using Semantic Model Scale Out. How? Let me explain…

Click through for that explanation.

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Creating a Custom Shape Map in Power BI

Published 2024-07-26 by Kevin Feasel

Elena Drakulevska builds a map:

Are you aiming for that WOW effect when your client opens your report? I’ve found that people often experience an immediate sense of awe when they see a map visual, especially when it’s conditionally formatted to highlight, for example, which country has the highest sales. So, I thought I’d share how you can achieve this and go beyond the built-in shape maps in Power BI. Let’s transform your global data into compelling visual stories!

Click through to learn more about the technique.

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Calculation Options in Power BI

Published 2024-07-23 by Kevin Feasel

Marc Lelijveld builds a list:

There are tons of options in Power BI to add your custom logic. Varying from SQL expressions at data ingest all the way up to Visual Calculations to add logic on a visual level. But how do they compare to each other, where should you do what?

As I’ve been a fan of making DAX easier since day one, I thought it may be a good moment to highlight the differences between calculation options using DAX in Power BI, like measures and calculated columns and how that is significantly different with Power BI Visual Calculations and how those can make your DAX easier.

Read on for a half-dozen options and some further thoughts about calculation options.

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Comparing Pie and Waffle Charts

Published 2024-07-22 by Kevin Feasel

Rita Fainshtein makes waffles:

Why is it more challenging to get an accurate answer from pie/donut charts and why do we feel less confident trying to read them?

The main reason is the difficulty in calculating the areas of the pie slices/lengths of the donut arcs.

This is much more challenging and less confident than comparing the areas of rectangular shapes.

Rita takes a look at the waffle chart custom visual available for Power BI and then builds something custom fit for the task.

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Color and Power BI Themes

Published 2024-07-22 by Kevin Feasel

Allison Kennedy talks color in Power BI:

Being a good data storyteller means using all the tools at your disposal. This includes color. It is important to note that I’m not advocating the use of color only in your reports – you need to ensure that there is another method to discern what’s going on with the data for those in your audience who might be colorblind. But that doesn’t mean we can’t play around with color and use it to add meaning to our reports. 

Most people I know would agree that GREEN means ‘Good’ and RED means ‘Bad’. But colors can be very personal. For example, my favorite color is BLUE and it was also the color I chose for my math notebooks throughout school. (Yes, math was my favorite subject – I guess it’s no surprise I ended up in a career that works so much with data.) 

In addition to personal meaning of colors, there can also be cultural meanings around individual colors, and that can shape how individuals view a given color. Grace Fussell has one of my favorite articles on the topic.

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One Problem with Scrollbars in Power BI

Published 2024-07-16 by Kevin Feasel

Chris Webb focuses on the performance aspect of scrollbars on tables:

Concluding my series of blog posts on seemingly harmless things you can do in a Power BI report that can lead to performance problems and the “This visual has exceeded the available resources” error (see also “Calculate(), Filter() and DAX memory usage” and “DAX measures that never return blank“), in this post I’ll show how table visuals with vertical scrollbars that potentially show thousands of rows can be a Bad Thing.

I’d also note the aesthetic problem: the intent of a dashboard is to be glanceable, meaning that a user can gain sufficient understanding of what is happening without needing to click, drag, sort, filter, or otherwise manipulate the dashboard. This means, if you are intending to create a dashboard (versus a report), vertical scrollbars form a second sort of issue: you’re obscuring data that you consider important enough to show to the end user.

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Visual Calculations and Multi-Bar Graphs

Published 2024-07-11 by Kevin Feasel

Erik Svensen builds a thing:

In this post I will guide you through creating this chart in Power BI – it is a stacked bar chart that show the size/impact of three different measures – Sales Value, Sales Units and Avg Price in one visual.

It’s not a visualization that I would recommend but there might be use cases for it somewhere and it has been a good exercise in what we can do with visual calculations.

It’s very clever, I’ll give it that.

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Automate the Power BI Incremental Refresh Policy via Semantic Link Labs

Published 2024-07-10 by Kevin Feasel

Gilbert Quevauvilliers needs to get rid of some data fast:

The scenario here is that quite often there is a requirement to only keep data from a specific start date, or where it should be keeping data for the last N number of years (which is the first day in January).

Currently in Power BI using the default Incremental refresh settings this is not possible. Typically, you must keep more data than is required.

It is best illustrated by using a working example.

Check out that scenario and how you can use the Semantic Link Labs Python library to resolve it.

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Antipattern: DAX Measures Never Returning Blank

Published 2024-07-08 by Kevin Feasel

Chris Webb explains the value of BLANK:

Following on from my earlier post on the Query Memory Limit in Power BI, and as companion to last week’s post on how a DAX antipattern using Calculate() and Filter() can lead to excessive memory consumption by queries (and therefore lead to you hitting the Query Memory Limit), in this post I want to look at the effects of another DAX antipattern on performance and memory usage: measures that can never return a blank value.

Read on to see how much of a difference using DAX to fill a grid with 0’s can make.

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Deploying a Power BI Project File via Azure DevOps

Published 2024-07-02 by Kevin Feasel

Angela Henry deploys to prod:

When it was announced there was a collective cheer from Power BI source control advocates heard ’round the world. Since it’s preview release, Microsoft has also added GIT integration with Fabric workspaces. This makes it so easy to incorporate source control for all (or almost all) of your Fabric artifacts, including Power BI.

But what happens when your organization already has a mature CI/CD process in place using Azure DevOps? Do you really want to break from that pattern and have it controlled somewhere else? That’s what this post is about, using Azure DevOps CI/CD pipelines to deploy your Power BI Project files (.pbip).

I’m going to share my experience in hopes that it will save you some time if this is the route you need to take.

Read on for Angela’s experience. Note that this applies both to Microsoft Fabric as well as a Fabric-less Power BI.

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