Power bi and how to organize your measures

 

Power Bi had gain significant traction in the business analytics space. Microsoft had proven to penetrate the market and successfully, introduced the app into a staple in the office productivity as well. In this article, I will not dwell into the history and the features of the tool. Instead, I will show you how to organize your power bi fields for easy and smooth dashboard development. 

Power Bi for dashboard

Yes, it is for that purpose and in the business analytics practice, this is a very useful tool. Seeing the numbers graphically and at a glance had proven efficient in drawing out insight and quick decisions. But, creating those highly interactive charts and graphs, could be harder than thought. 

The development could be messy and to produce that summary or data point could involved layers of calculation.

Navigating in the Development phase

Developing a power bi dashboard could be straightforward ( as what Microsoft intends it to be ). Just a heads up though, you could get lost in the sea of data fields as you get to dive in this application. Most times you will have to need to create customer formulas to draw certain calculation. This customize calculation is what we called as Measures.

Measures

There are actually two types and the are;

• Quick Measure - this is a preset formula most of them are self explanatory such as rolling averages.
• Custom Measure - this is an outright creation of the formula. Pretty much same as having one in a spreadsheet.

How to organize your measures?

Dealing with multiple fields on your data can be confusing. At some point, as you created multiple measures, unknowingly you've duplicated some. So, how do you manage this kind of scenario and somehow create an efficient way of navigating your measures.

Two ways to "5S" your measures

• Folders - this is the most effective approach. Containing your measures into a folder see below for the demo
  
• Simple prefix - this is just a personal labeling approach that I've done which is also effective. Example below shows "#_" as prefix. In this way, I have all measures at the top of the field list. It's helpful for I tend to create more measures when developing PowerBi dashboards. 

Being effective with PowerBi is basically doing 5S on your back-end. The foundation to create useful dashboard starts with sustainable Power Bi desktop (.pbix) files. Making your data fields tidy and easy to navigate is key in the development phase. How about you? Do you have any better approach? Let us know in the comment section below.