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.

Example

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

Method

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DAX CALCULATE Debugger

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:

DAX CALCULATE Debugger

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 ūüėČ

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Memory efficient clustered running total in Power BI

Today I want to share a scenario where a running total calculation in the query editor saved a model that run out of memory when done with DAX:

Problem

The model couldn’t be refreshed and returned out of memory error with a calculated column in the fact table of over 20 Mio rows (from a csv-file). A running total should be calculated for each “JourneyID”, of which there were over 1 Mio in the table itself. This rose memory consumption during refresh by over 300 % – until it finally errored out:

Besetzung =
CALCULATE (
    SUM ( Fact[Entries] )
–¬†SUM¬†(¬†Fact[Exits]¬†);
    FILTER (
        ALLEXCEPT ( Fact; Fact[JourneyID] );
Fact[StopId]
<= EARLIER ( Fact[StopId] )
    )
)

Solution

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Right Aligning Text in Power BI: Format Improvements for Easy Profit&Loss Reports

Edit 14-Dec-2017: Now that we can right-align text measures in PowerBI, a SWITCH-measure like here: http://www.thebiccountant.com/2017/04/24/kpis-in-easy-profit-and-loss-for-powerbi/#comment-719 is the best alternative in my eyes. No need to read on ūüôā

As shown in my last part of the Easy P&L-series, Power BI unfortunately still lacks some fundamental formatting options like:

  1. Right aligning text (please vote for it here: Right align text in Power BI¬†– edit 15th Nov: We’re there: Right aligning text is available now: https://powerbi.microsoft.com/en-us/blog/power-bi-desktop-november-2017-feature-summary/)
  2. Display numbers in different formats within one column (either to be implemented as a “neutral” format for Switch-measures, where the referenced measures carry the formatting attributes already, or as a part of a formula-based conditional formatting) (Thanks Matt for the voting-link: Conditional format SWITCH measure)

So for the moment I choose between the following workaround-options:

  1. Display %-values in a separate column
  2. Format numbers as text and fill up with spaces so that all end up right aligned
  3. See the suggestion from Matt Allington in the comments below (very nice)

Right aligning text or percentage figure in new column

For both options the preparations are the same:

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Bill of Material (BOM) Explosion Part2: Costing in Excel and PowerBI

Following up on the BOM-explosion: A comment reminded me that I had missed to present the costing techniques to calculate the total costs of each (sub)-product.

Reversing the aggregation direction

What I had shown¬†is how to¬†“aggregate” from parent down to child-level to retrieve the total quantity of each component within a BOM (“How many of each (sub-) components do we have to order (or build) for that bike?”) (1).

Now we reverse the aggregation direction and aggregate the total (!) quantities back up to the parents (2).

And, as this doesn’t make too much sense in an economical way, the second aggregation will be¬†their prices (3). This will give us the sum of all part-costs (“How much will the order of all the parts cost us?”). This is also very useful for planning purposes or reconciliation of prices¬†for intermediate products with your master data.

And if your model holds sales-data as well, you can calculate the totals costs of your total sales within each period. (4)

VAR 1: Using classical hierarchies

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