Organize Your DAX Measures in Power BI


Like many others, I wrote my first DAX measures in Excel Power Pivot. It seemed so natural to add measures in the editing area associated with the fact table I never considered any other way. But while measures specify one or more tables in their code definition, there is really no restriction on "where" they may be defined. We can use this fact to make measures easy to find and use in the Power BI desktop environment.
We start by creating a table that is destined not to hold any row data at all. In this example, I will bring up Power Query and choose "Edit Data" from the menu.

choose "Edit Data" from the menu

I'll type in any value and name the table SalesMeasures. After applying the changes and returning to the Power BI desktop, as few or as many measures as we wish can be added to this new "table".

creating table screenshot

For this example, I'll create two measures, MedianSalesAmount and 90th Percentile SalesAmount.

90th Percentile Sales Amount = PERCENTILE.EXC(Sales[SalesAmount], 0.90)

MedianSalesAMount = MEDIAN(Sales[SalesAmount])

Now that we have some measures, we really don't need any rows or columns in the table at all. We can delete "Column1" from the SalesMeasures table. Note that at present the SalesMeasures table is in the "S" section of the fields list, and the icon is like that of any other table.

SalesMeasures table is in the "S" section of the fields list

We can now save our work, then close and reopen the Power BI workbook.

reopen the Power BI workbook

When we reopen the workbook, we note that because there is no row data, the SalesMeasures table has moved to the top of the fields list and the "table" icon has been replaced with the measure icon. Users no longer have to search for particular measures; they're all together at the top of the tables list.

Dan Buskirk

Written by Dan Buskirk

The pleasures of the table belong to all ages.” Actually, Brillat-Savaron was talking about the dinner table, but the quote applies equally well to Dan’s other big interest, tables of data. Dan has worked with Microsoft Excel since the Dark Ages and has utilized SQL Server since Windows NT first became available to developers as a beta (it was 32 bits! wow!). Since then, Dan has helped corporations and government agencies gather, store, and analyze data and has also taught and mentored their teams using the Microsoft Business Intelligence Stack to impose order on chaos. Dan has taught Learning Tree in Learning Tree’s SQL Server & Microsoft Office curriculums for over 14 years. In addition to his professional data and analysis work, Dan is a proponent of functional programming techniques in general, especially Microsoft’s new .NET functional language F#. Dan enjoys speaking at .NET and F# user’s groups on these topics.

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