The earlier publish defined what Skinny stories are, why we must always care and the way we will create them. This publish focuses on a extra particular matter, Report Degree Measures. We talk about what report-level measures are, when and why we want them and the way we create them.

If you’re unsure what Skinny Report means, I counsel you take a look at my earlier weblog publish earlier than studying this one.

What are report degree measures?

Report degree measures are the measures created by the report writers inside a Skinny Report. Therefore, the report degree measures can be found inside the internet hosting Skinny Report solely. In different phrases, the report degree measures are domestically out there inside the containing report solely. These measures aren’t written again to the underlying dataset, therefore not out there to some other stories.

In distinction, the information mannequin measures, are the measures created by information modellers and seem on the dataset degree and are unbiased from the stories.

Why and when do we want report degree measures?

It’s a widespread state of affairs in real-world situations when the enterprise requires a report urgently, however the nuts and bolts of the report aren’t being created on the underlying dataset but. As an illustration, the enterprise requires to current a report back to the board exhibiting year-to-date gross sales evaluation however the year-to-date gross sales measure hasn’t been created within the dataset but. The enterprise analyst approaches the Energy BI builders so as to add the measure, however they’re below the pump to ship another functionalities which including a brand new measure just isn’t even of their undertaking supply plan. It’s maybe too late if we anticipate the builders to plan for creating the required measure, undergo the discharge course of, and make it out there for us within the dataset. Right here is when the report degree measures come to the rescue. We are able to merely create the lacking measure within the Skinny Report itself, the place we will later share it with the builders to implement it as a dataset measure.

How can we create report degree measures?

Presently, we will create report degree measures solely in Energy BI Desktop when Join Reside to both a Energy BI dataset, an SSAS Tabular mannequin (on-premises), or Azure Evaluation Companies (AAS). For this weblog publish, I Join Reside to a Energy BI dataset. Open Energy BI Desktop first and comply with these steps.

1. Click on the Information hub dropdown button from the Residence tab
2. Click on the Energy BI datasets
3. Choose the specified dataset
4. Click on Join

5. Proper-click the desk that you just’d prefer to host the report degree measure and choose New measure

6. Sort your DAX expressions as common and press enter

A brand new measure (Avg Unit Value) is now created on the Web Gross sales desk. As defined earlier, the brand new measure is simply out there within the present report and never on the dataset degree and that’s the reason any such measure is the so-called Report Degree Measure. All different measures are dataset degree measures, subsequently, they’re out there on the present report and some other skinny stories we create sooner or later on prime of the identical dataset.

We are able to now use the Avg Unit Value as common in our information visualisation.

As maybe have seen already, we will additionally create report degree measures utilizing the Fast Measures functionality.

As a aspect notice, you too can see the underlying information mannequin by clicking the Mannequin view tab as proven within the following picture:

Have you ever used this functionality? What challenges have you ever confronted in utilizing Report Degree Measures? I’d like to know your ideas, so be at liberty to depart your feedback under.