Tidy up Power BI models with the Power BI Cleaner tool

Edit 23th June 2020: Updated version (see download link at the end of the article) to reflect changes with the vpax fileformat in DAX Studio versions V11.0 upwards.

The VertiPaq-Analyzer tool is one of the great community tools that I really cannot live without. It gives me a great overview of all elements in my model and identifies potential performance problems by showing the storage requirements of each column. So when seeing expensive columns, the first question that arises is: “Do I really need this column or could I delete it?”. Luckily, this can now be answered with my new Power BI Cleaner tool. This tool shows the usage of all columns (and measures) within the tables of the VertiPaq Analyzer.

Power BI Cleaner shows unused columns in the VertiPaq-tables

Power BI Cleaner tool

So whenever there is no entry in the column “Where Used” you can go ahead and eliminate the column (or measure) from the model. Well – with one exception actually: Fields used in the definition of incremental load policies are currently not identified. So make sure to consider this before running wild 😉 Read more

Compare Power BI files with Power BI Comparer tool

Update: This solution will currently not work with the new enhanced metadata format, that’s currently in preview in Power BI!

Have you ever wanted to compare a version of a Power BI file with a previous one? … In the unlikely case that you haven’t yet, just wait until the auditors are in again – my new Power BI Comparer tool will save your day then 😉

Or maybe even before you uploade a new version of a report that has already been published to the service. How do you communicate the changes to your colleagues? Wouldn’t it be nice to have a tool that performs that comparison and documentation fully automagically?

Power BI Comparer

Fortunately my Power BI Comparer-tool makes it super easy to compare all properties of 2 Power BI files with each other: Just convert your pbix-files to pbit (as we need to access the data model properties as well) and drop the paths to these new files in my Excel-file like so:

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Debug DAX variables in Power BI and Power Pivot

When you’re dealing with a beast like DAX you can use any help there is, right? So here I show you how you can debug DAX variables who contain tables or show the result of multiple variables at once. So you can easily compare them with each other to spot the reason for problems fast.

Please note, that currently only comma separated DAX code is supported.


Watch this measure from Gerhard Brueckl’s brilliant solution for dynamic TopN clustering with others. It contains 5 variables who return tables and one variable with a scalar:

Measure with variables who contain tables and scalars

If you want to follow along how this calculation is evolving for each value in a matrix, my VarDebugMeasure will show details of every variable like so:

Measure to debug DAX variables


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CALCULATE is the most powerful function in DAX, as it allows you to change the filter context under which its expression is evaluated to your hearts content. But with big number of options to choose from, often comes big frustration when the results don’t match expectations. Often this is because your syntax to modify the filter context doesn’t do what you’ve intended. Unfortunately CALCULATE only displays its result and not how it achieved it, so debugging becomes a challenge. This is where my CALCULATE Debugger measure can help out:


This is a measure that returns a text-value, showing the number of rows of the adjusted filter context table, the MIN and MAX value of the selected column as well as up to the first 10 values. Just place this measure beneath the CALCULATE-measure in question and try to find the error 😉

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