Category: Power BI

Alberto Ferrari has a great explanation of how the concept of expanded tables works in DAX:

If you are coming from an SQL background, or if you are used to relational databases, you probably think that RELATED follows relationships. Thus, to compute the Month column, you would think that the engine followed a relationship between Sales and Date and obtained the value of the month by performing a lookup on the Date table.

DAX is different. Date[Month] belongs to the expanded version of Sales, There is a value for RELATED(Date[Month]) because Sales was expanded to include Date using a relationship.
RELATED requires a row context to be active. If you remove the row context of the calculated column, then RELATED no longer works.

This post cleared up a couple of ideas in my head, so check it out.

Stacia Varga has a post covering some of the yeoman’s work of data cleansing:

For now, Power BI continues to my tool of choice for my project. My goals for today’s post are two-fold: 1) finish my work to address missing venues in the games table and 2) to investigate the remaining anomalies in the games and scores tables as I noted in my last post.

To recap, I noted the following data values that warranted further investigation :

• Total Goals minimum of 0 seems odd – because hockey games do not end in ties. I would expect a minimum of 0 so I need to determine why this number is appearing.

• Total Goals maximum of 29 seems high – it implies that either one team really smoked the opposing team or that both teams scored highly. I’d like to see what those games look like and validate the accuracy.

• Record Losses minimum of 0 seems odd also – that means at least one team has never had a losing season?

• Similarly, Record Wins minimum of 0 means one team has never won?

• Record OT minimum of 0 – I’m not sure how to interpret. I need to look.

• Score minimum of 0 seems to imply the same thing as Total Goals minimum of 0, which I have already noted seems odd.

This is the kind of stuff that we talk about as taking 80-95% of a data science team’s time.  It’s all about finding “weird” looking values, investigating those values, and determining whether the input data really was correct or if there was an issue.

Cedric Charlier shows how to ignore case when running Table.Distinct in Power Query:

Note that at the top of the table, I’ve twice the value ADO.NET, once with uppercase and once lowercase for the “Net” part. If I try to apply a Table.Distinct, the two values will be considered as distinct and one of them won’t be removed.

Will it be an issue? If this your key and it’s part of a model where this key is part of one side of a one-to-many then it will be an issue.

Read on for the solution.

Paul Turley goes on a rant:

Makes perfect sense, right?  This is a basic use case and a good application for simple KPIs; with the one minor caveat that POWER BI DOESN’T SUPPORT THIS!

This topic has become a bit of a soapbox topic for me because it’s a capability that, in my opinion, is a very obvious gap in the Power BI feature set.  After unleashing my rant, I’ll demonstrate a solution a little further down in this post.

Both the rant and the workaround are interesting enough to read, so check them out.

Wolfgang Strasser shows how to display the parameters selected for a Power BI report on the report itself:

Dataset Parameters are a way to bring some sort of dynamic into your Power Query datamodelling in Power BI. For my blog post about  Modifying Parameter values in powerbi.com  I was looking for a way to display the value of a parameter inside a Power BI report.

In this blog post I would like to show you the steps that are required to bring your parameters to your field list  – and as a consequence – into your Power BI report.

Read on to see how to do this.