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Discovering patterns in your data is one of the many amazing things you can do within Power BI. Ultimately, with the use of Power BI visualization features, you can showcase patterns in your data effectively.
I’ve already shared a lot of content on this topic. You can read the article I wrote about some techniques you can use to discover patterns in your data using DAX in Power BI. Another related article I posted explains how to detect anomalies and outliers in your data.
I highly recommend that you read these articles, as they include video tutorials that could help you better understand the DAX and visualization techniques I use to achieve this kind of analysis.
In addition to those tutorials, I’d like to share with you my in-depth discussion on analyzing and showcasing patterns in your data or what I call, a cluster analysis visualization.
This is a break-out session from one of the Enterprise DNA Learning Summit workshops. Here I dive into how you can showcase data clusters or patterns in Power BI and how they change through time. I incorporated many DAX concepts and visualization techniques in this tutorial.
If you want to go deeper and more advanced in analyzing data patterns and outliers, I recommend you this next tutorial.
In this tutorial, I take Power BI development to the next level and show you how to discover significant new trends in your data. I go through some advanced logic in Power BI using DAX.
Here I explain the differences between raw and filtered contexts. I also demonstrate how you can identify and showcase outliers dynamically in Power BI.
If you’ve noticed, the best way to showcase data patterns, outliers, and anomalies is by using the scatter chart or scatter plot. It’s one of the visualizations inside Power BI. If you want to know more about this visualization, here’s a comprehensive tutorial explaining how to use it and its built-in analytics efficiently.
If you have a lot of data, your scatter chart can end up being really busy, consequently, it would be difficult to see patterns of information clearly. That is why, I’ve developed a strategy to break out the scatter chart of information, showing specific patterns or outliers. All the techniques involved are shown in the tutorials and related links that I’ve included in this post.
Key Takeaway
Analyzing patterns in your data and presenting them in scatter charts effectively will help you understand why they are occurring. You can also improve your business strategies and make things right.
I hope you’ve learned a lot from this. There are some pretty advanced DAX combinations and logic involved; there are also some great visualization techniques using scatter charts.
There are so many applications for data pattern analysis and outlier detection. If you can understand all the elements of the formulas, combining and placing them inside a visualization, you can apply this in many ways to showcase results with your own data sets.
For more information about the topic, check out the links below.
All the best!
Sam
***** Related Links *****
Finding Patterns In Your Data Using Internal Logic in Power BI
How To Evaluate Clusters in Your Data Using DAX Technique in Power BI
Detecting & Showcasing Outlier Results In Power BI
***** Related Course Modules*****
***** Related Support Forum Posts *****
Outliers Help. Can’t See My Non-Outliers On Scatter
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