I hadn’t explored much in the way of custom visuals in Power BI until a while back, even though I was very much aware of the competition that was held in September. It had been on my list to explore some of what was possible. And this month, the T-SQL Tuesday topic (hosted by Wendy Pastrick – @wendy_dance) was to learn something new and to blog about it. So it seemed a good idea to learn how to make my own custom visualisation!
Now, creativity isn’t exactly my thing. I find it really hard to write songs, for example. I know how to do it – but I quickly become self-critical and get stuck. Writing is easier, because it feels less ‘creative’, and appeals more to the teacher / preacher in me (and I know that takes creativity, especially if you’ve ever seen me present, but it’s different). So sitting down and coming up with a new way of visualising data wasn’t something I was going to do.
You can download the workbook here if you want to take a look, or simply look at the embedded version I have pinned at the bottom of the post.
Notice the spikes in sales in different months in the chart above? These spikes are very common in sales data, and in my experience they can be even more prevalent in weekly sales data. These spikes make it difficult to analyse trends in the data. You could put a trend line into the chart (thanks to the April update do Power BI), but a standard linear trend line is too simplistic to really see what is happening in your data, particularly if there are seasonal changes.
One good way to look at the trends in your data is to add an Average Monthly Sales Rolling Quarter trend line to the chart. You simply take the total sales of the last 3 months and then divide by 3. If you were doing a weekly trend, take the last 13 weeks and divide by 13. When you overlay this Avg Monthly Sales RQ line on the original chart, it looks like this.
This is a fairly advanced topic, but it’s also the kind of thing which separates good reporting from great reporting.
Beautiful data visualizations reveal stories that numbers just cannot simply tell. Using visualizations, we can get a sense of scale, speed, direction, and trend of the data. Additionally, we can draw the attention of the audience – the key to any successful presentation – in a way that’s impossible with tabulations. While a tabular view of new online signups is informative for tracking, a dynamic map would provide a more captivating view and reveal dimensions that a table cannot.
Hence, I worked on a map visualization that depicts signups in real time. In this post we will walk through the tools used to construct this map and discuss the technology that allows the frontend to listen and to receive data from the backend. The code should be sufficient for the readers to build their own flavor of the real-time map visualization. Note that I’m not a front-end developer. I did this for the sake of curiosity!
We’ve seen Power BI achieve the same goals (e.g., here and here), but this lets you write some custom code to fit into applications. On the database side, we tend not to think so much about good internal monitors. We buy monitoring tools for our databases, but those don’t tell us if our applications are healthy.
But what about if you want the chart title to change depending on what is selected? For example, you might be using slicers or filters to allow a user to choose which days of the week they want to see data for. In that situation you might want to add a title that shows which days of the week have actually been selected; this would be particularly important if the report uses filters, or if the report is going to be printed. Unfortunately the built in Title Text property can’t be used to display dynamic values but in this blog post I’ll show you how to solve this problem using DAX.
The solution isn’t trivial, but it is cool.
Do you know the difference between a blue pill and a green pill? What happens when you add a green pill to the color shelf? Pills, cards, and shelves are the foundation of Tableau visualizations. If you are new to Tableau or have been playing around with it but not quite sure how to get the view to look the way you want, we have a video for you! In this video, I’ll help you understand pills, cards, and shelves so instead of wondering “Why did Tableau do THAT?” you’ll be in better control of what you want Tableau to do.
Power BI and Reporting Services 2016 are exciting technologies, but there’s a wide world outside of Microsoft, and Tableau is a major player in the world of visualization.
This is one of the coolest custom visuals I’ve seen so far. The reason is that this custom visual has a customization in it! with this visualization you can define regions in any picture or images, and map data points to the image in your Power BI report. The image can be everything; human body, airplane seat layout, shop floor layout or football field. You choose the image you want, then you define regions. Let’s have a closer look at this visual.
It’s amazing how easy Power BI makes that. Almost easy enough for me to do it…
Yeah, that’s a DAX-powered, Power BI dashboard, right here in our website – a website that runs on WordPress, which is Linux for crying out loud. Don’t know what Linux is? No worries, just translate it as “there’s zero Microsoft software behind PowerPivotPro.com, and yet – BAM! Power BI, right here!”
And the dashboard in question is a near-real-time view of the traffic on this very site! Check back in an hour and you will be able to “see” yourself on the map (especially easy if you use one of the “rarer” browsers.)
Check out the technical walkthrough if you’re interested in doing something similar yourself.
However, it seems that there might be two kinks in the line:
The first kink occurs somewhere between the 800m distance and the mile. It seems that the sprinting distances (and the 800m is sometimes called a long sprint) has different dynamics from the events up to the marathon.
The analysis is done in R, and the code is available in the post. Check it out.
But R is also part of an entire ecosystem of open tools that can be linked together. For example, Markdown, Pandoc, and knitr combine to make R an incredible tool for dynamic reporting and reproducible research. If your chosen output format is HTML, you’ve linked into yet another open ecosystem with countless further extensions.
Generating a page from R is one of those good ideas that I probably don’t want to see in a production environment.
Not only can we create and download custom visuals from PowerBI.com to extend the capabilities of Power BI, we can use R to create a ridiculous amount of powerful visualizations. If you can get the data into Power BI, you can use R to perform interesting statistical analysis and create some pretty cool, interactive visuals.
Dustin and Jan Mulkens are working on similar posts at the same time, so watch both of them.