Category: Power BI

Matt Allington explains what the ALL() function is in DAX and when you might want to use it:

The ALL() function seems very simple on the surface however it has layers of complexity.  In its most simple usage it is a function that simply returns a table (virtual or materialised).  The syntax for ALL() is as follows

=ALL(TableOrColumn,[Column2],[ColumnN]..)

ALL() will always return a table, not a value.  Because it is a table, you cannot put the result directly into a cell in a Pivot Table or a Matrix.  Think about it, you can’t put a table with (potentially) multiple columns and (potentially) multiple rows into a single cell in a visual – it wont “fit”.

There’s a lot to ALL() and Matt does a great job explaining it.

Matt Allington explains how to use the Combine feature in Power Query:

Now the good news is that somehow the combine button has done a reasonable job at combining the files (see 1 below).  Actually I wanted to unpivot the month columns, but I will come back to that later.

The bad news is all of the activity over on the left hand side.  What the…?  There are 5 additional “Queries” on the left (numbered 2 – 6) that do all sorts of things.  Let me tell you what each of these are and then come back and explain how to use/interpret these things.

2. This is a parameter that can be used to change the sample file

3. This is the link to the sample file that was selected originally (I selected the first file in the folder and this is the link to that file).

4. This is the “by example query” – the most important query to know about.

5. This is an auto generated function that goes with 4 above.

6. This is the final output query (it is the query that is displayed in 1 above).

Matt clearly explains the whole process, so read on if you need to combine files of Power Query.

Philip Seamark shows how to bundle measures together in Power BI so they all appear at the top of the Fields section:

I’m going to share in this blog a technique I’ve found useful in Power BI for collecting measures together in once place AND placing them at the top of the field list.

The good news is, calculated measures do not have to exist on the table that stores the underlying data specific to that measure.  Measures can be placed on any table in the model and they will still work as expected.  This may not be immediately obvious but it’s handy to know.

So far, I’ve kept measures on their logical best-fit tables, but Philip’s hint looks quite useful once the set of measures grows, or if there are a number of cross-table measures.