Category: Visualization

Meagan Longoria compares and contrasts:

One of the new features in the August Power BI Desktop release is the updated legends that are styled to more accurately reflect the per-series formatting on the visual. This made me curious how close I could get to the clean look of a Deneb (vega-lite) stacked bar chart.

I used open source data from the Vega github repo and applied a few filters in Power BI. I used exactly the same source data in each chart, filtering down to five sites and 9 varieties. I chose a visual with a legend, data labels, and total labels to display the differences. We can argue about whether you should show a chart with this many labels another day.

Click through to see how the in-built visual compares to a custom visual of the same form.

Martin Schoombee explains the challenge of dashboard review:

A little while ago I was asked to rate a Power BI dashboard. The person who asked, participated in a Power BI challenge (I’ll call it that because that’s the way they are being marketed) and wanted some feedback on the submission. I agreed on the condition that the feedback would be public and in the form of a blog post.

Martin has a thoughtful explanation of the difficulty of providing a review (especially without important context around what the end users intend to do) but then does yeoman’s work talking about the visuals.

Kurt Buhler points something out:

Effective visualizations provide context so that you can interpret the numbers and what they mean to you. Is this number bad or is it good? This is particularly important for visuals that aim to provide a quick, 3-second overview, like cards, KPIs, and simple trendlines. You can provide context by comparing to a target, but if no target is available, you can also compare to a measure of central tendency, like the average or median. However, instead of comparing to an aggregate, you might also want to compare to other categories.

Consider the following example, which shows the desired end result for this article: a plot which highlights a selected value so that the user can compare it to all others. This example uses some DAX and formatting with a line chart and scatterplot to achieve the result of a joint plot atop a jitter plot. If you want to learn more about what a joint plot or a jitter plot is, we gave an overview of these and similar chart types in a previous article.

This is something I find frustratingly difficult with Power BI. Kurt does a great job of showing how to get there, but it seems like it should be a lot easier to do.

Erik Svensen knows what day it is:

Last week I posted on LinkedIn an example on how we can utilize the matrix as a month calendar slicer.

It got a lot of attention so why not share an example file where you can see how I built it.

Erik has put the sample file in a GitHub repo, so click through to check that out.

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.