Don't miss your chance to take the Fabric Data Engineer (DP-700) exam on us!
Learn moreNext up in the FabCon + SQLCon recap series: The roadmap for Microsoft SQL and Maximizing Developer experiences in Fabric. All sessions are available on-demand after the live show. Register now
Hello!!!
These are items that come from different manufacturers.
Each manufacturer offers a different discount for the purchase of their items.
We have a table with 4 columns: Item, manufacturer, item&manufacturer and discount.
You would need a 5th column where the purchase priority appears.
That is, product 105 is produced by 4 different manufacturers; From manufacturer 1 I can get 62% discount, from manufacturer 2, 60%, from manufacturer 3 40% and manufacturer 4 30%.
In case the same item has the same discount in different manufacturers the priority must be the same.
| ARTICLE | MAKER | ART&MANUFACTURER | DISCOUNT | PRIORITY |
| 105 | 1 | 105 // 1 | 62 | 1 |
| 105 | 2 | 105 // 2 | 60 | 2 |
| 105 | 3 | 105 // 3 | 40 | 3 |
| 105 | 4 | 105 // 4 | 30 | 4 |
| 277 | 1 | 277 // 1 | 62 | 1 |
| 277 | 2 | 277 // 2 | 60 | 2 |
| 277 | 4 | 277 // 4 | 60 | 2 |
Thank you very much in advance for your help.
Solved! Go to Solution.
Hi,
I am not sure how your datamodel looks like, but please check the below picture and the attached pbix file.
Priority measure: =
IF (
HASONEVALUE ( Data[ARTICLE] ),
RANKX (
FILTER ( ALL ( Data ), Data[ARTICLE] = MAX ( Data[ARTICLE] ) ),
CALCULATE ( SUM ( Data[DISCOUNT] ) ),
,
DESC
)
)
Hi,
I am not sure how your datamodel looks like, but please check the below picture and the attached pbix file.
Priority measure: =
IF (
HASONEVALUE ( Data[ARTICLE] ),
RANKX (
FILTER ( ALL ( Data ), Data[ARTICLE] = MAX ( Data[ARTICLE] ) ),
CALCULATE ( SUM ( Data[DISCOUNT] ) ),
,
DESC
)
)
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 50 | |
| 44 | |
| 42 | |
| 19 | |
| 19 |
| User | Count |
|---|---|
| 70 | |
| 68 | |
| 33 | |
| 32 | |
| 32 |