Secondary Table Logic Techniques Using DAX In Power BI – Advanced DAX

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In this tutorial I’m going to run through a really cool topic within Power BI and the DAX formula language that I call secondary table logic.

Sometimes when using Power BI for your analytics you’ll want to find or unearth interesting insights but the current data you are working with may not allow you to extract such insights.

Which is why sometimes it is crucial to create what I call secondary tables to bring in such information to your core data model.

In this video tutorial, I show from start to finish how you need to think analytically about utilizing these tables, but then also how to implement them in a really practical way.

We learn better by doing and so, I will take you through a practical example of how you can go about doing this on your own and show you how you can bring in various information or insights to your data analysis that really showcases things in a much more effective way.

The video contains all the tips you need to be able to grasp this unique concept in Power BI. These techniques are actually quite unique to Enterprise DNA and to some of the best practice development that we’re completing.

It is only after you watch this that you’ll get to understand exactly what I mean. So go ahead, review the video, I can promise there is a lot to learn.

Your mind will expand exponentially in terms of the analysis and information that you can get into your reports.

If you want to check out even more advanced analytical techniques that you can learn in Power BI certainly check out this module at Enterprise DNA Online. You’ll be amazed at what you can achieve analytical using Power BI.

Advanced Analytics in Power BI

Good luck!

Sam

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2 comments on “Secondary Table Logic Techniques Using DAX In Power BI – Advanced DAX”

  1. This is great to know how to do dynamic segmentation with a measure, combined with the other video about an inline SWITCH for a calculated column. I’ve got an immediate use case to apply these techniques to – peak/off-peak times using specific event times converted to 30 minute increments that then need to be segmented into multiple peak and off-peak groupings.

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