I know how to do the calculation in my head as I've been doing it in Excel however, I was having trouble translating it into DAX. Your tutorial definitely helped putting it into perspective. Also, I'm glad there is already DAX Query View in Power BI, which really helped in visualizing the virtual tables.
Thank you for this great video! I'm wondering, if instead of highlighting on the chart the complaints accounting for the chosen threshold we want to count the number of complaints contributing to the chosen threshold, how would we do it? For example: I want ameasure to return the number 4 if the complaints are: Order mix_up, website not working, absence of modes of payments, long wait time.... Thanks!
This is amazing. Unfortunately this gets extremely computationally expensive in my scenario. I am ranking warehouse picks by material, and just so far in 2024 I have 2,653 unique part numbers. This measure works out great, and the tie-breaking works well. What I am unable to figure out is a second measure to calculate the number of materials where the Pareto % is less than or equal to 80%: Pareto Material Count = CALCULATE( DISTINCTCOUNT('WarehousePickTable'[Material]), FILTER( 'WarehousePickTable', [Pareto %] >= 0.8 ))
Hello thank you! But I still have one question left, how do I save the pareto threshold value. I did it with SELECTEDVALUE, but this only works for a slicer which is not between, >= or
Great Video, one question- wondering why MAXX was used in line 12 instead of MAX (for variable __CurrCompPos ), as there is no row level iteration happening for table __CompTable.
Good question! __CompTable is a table variable, to extract a value from a column in a table variable, you need to use an iterator function. MAX would work if you refer to a physical table. Hope it made sense.
my only problem with using ADDCOLUMNS with the pareto measure is that when a subcategory is present in the model and it is being filtered, i'm getting a blank. i had to use SUMMARIZE to fix that.