Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowJuly 7 - July 17 | Round 2 of the Power BI Dataviz World Championships. Don't miss your chance! Learn more
Hi,
I've attempted various DAX statements in order to generate measures and columns that would create a summarised table visual, but I'm encountering difficulties in achieving the desired outcome.
My goal revolves around a table visual, labeled as Fig1, which employs four fields extracted from a table named "Allocations." Presently, this table contains 240 rows, although this count can fluctuate throughout the month.
My objective entails evenly distributing the RankT values into three distinct groups: Good, Normal, and Bad. Subsequently, I aim to identify the highest and lowest Conversion Percentages within each of these groups.
Ultimately, my aim is to generate a table visual resembling the one depicted in Fig2 and it needs to work with a selected values from a slicer. Despite my efforts, I'm struggling to realise this vision using DAX statements.
Name - column
Allocations - calculated measure
Conversion - calculated measure
RankT - calculated measure
Fig1
Fig2
Solved! Go to Solution.
Take a look at this article on ABC Classification. It should help you get what you are looking for.
https://www.daxpatterns.com/abc-classification/
Take a look at this article on ABC Classification. It should help you get what you are looking for.
https://www.daxpatterns.com/abc-classification/
| User | Count |
|---|---|
| 23 | |
| 22 | |
| 20 | |
| 20 | |
| 12 |
| User | Count |
|---|---|
| 63 | |
| 56 | |
| 47 | |
| 44 | |
| 37 |