Explore Forecasting Logic In Your Power BI Models Using DAX

Explore Forecasting Logic In Your Power BI Models Using DAX


It doesn’t get more real world than the video below for an application of Power BI to provide great insight. In the example I run though here, I want to compare my actual results to my forecasted results. Not only that – I want to view these cumulatively. The cumulative totals give me a much better overview and makes sure that as a trend is appearing, I know about it. Using the techniques I discuss in the video, you can achieve the same thing.

First though we need to create the actual forecast. You may have this in a separate data source or spreadsheet, or you may need to create it because you don’t have one already. There’s plenty of ways you can create one. Sometimes it can be simple; sometimes complex (overly so, in my opinion). Anyway, once you’ve got that set up, developing some simple logic and utilizing formulas with DAX can really give you insights into your data.

Remember that reviewing actual results by themselves is fine in some cases, but in many other instances you need a benchmark to really showcase the relative performance.

Unless you have a thorough understanding of the numbers, using a benchmark or forecast (as in this case) is the best way to showcase this for your consumers.

By also using the many other filters in your data model, you can set up your reports to very effectively dive into specific areas of your datasets and see how the results have performed vs the unique benchmark. There are sometimes some nuances to understand regarding the modeling of your data here, but that’s for another video tutorial.

It’s all about the business applications with this. I actually cover a lot of similar applications around forecasting and much more in my Solving Analytical Scenarios virtual course at Enterprise DNA Online. This is worth checking out if you want to explore forecasting, budgeting, grouping techniques as well as scenario analysis and others.

Hope you can find a way to get this analysis into your models.

All the best with this one.


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