I’m getting complex today with DAX, but that’s because I enjoy showcasing the power of this formula language inside of Power BI. I want you to get there too. It’s why I always want to get practical around implementation. This is a perfect example of a really valuable commercial insight you can extract out of your analysis in Power BI.
Say you want to see which customer groups are buying your products. When I say customer groups, is it your top customer, your middle-of-the-range customer, or your bottom customers? You’ll quickly discover this is not actually that easy to work out, as this ‘grouping’ doesn’t even exist in your raw tables. You need to create it via a supporting table, and I show you how in the video.
You then have to iterate through it for each different customer result, and I show you how to do this too.
Then you have to visualize it.
As you can see, there’s a bit to it, no doubt, but it’s really powerful stuff.
This analysis is great to see the make up of who is buying your stuff, not only across your products as a whole, but you can even dive into specific products and compare how the make up might be different.
This technique has a technical term – dynamic segmentation. It’s because we are dynamically segmenting our results by placing them through some logic which will slice it up into its own pie.
I run through this particular technique in a comprehensive way in my Solving Analytical Scenarios course at Enterprise DNA Online. Check this out to learn more. In this video, I run through an overview of how you could implement it yourselves and how it may look in your reports.
Good luck implementing this one.
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