Forum Discussion
Dynamic Classification with two criteria
- 6 years ago
Hi az38 , Thanks for your effort. The criteria to classify towns is as follows ;
- we are applying 80/20 formula here in segments, so when we are cumulating volume contribution% then top 80% ( in descending order) data will look like this
- so segment will always be in slicer. you can see that i have sorted data in descending order to get top % volume contributed towns. now we need to classify towns as per below criteria :
- If volume contribution is till 80% and market share of "My Company" in the town is >= "My Company's Total Share" in the segment then "Stronghold"
- If volume contribution is till 80% and market share of "My Company" in the town is < "My Company's Total Share" in the segment then "Headroom"
- If volume contribution is till remaining 20% and market share of "My Company" in the town is >= "My Company's Total Share" in the segment then "Emerging"
- If volume contribution is till remaining 20% and market share of "My Company" in the town is < "My Company's Total Share" in the segment then "Small"
- its like 0% to 80% then 81% to 100% (since we have already sorted data in top to bottom). I want to approach this by using "DESC" formula so that it would always be dynamic whenever i am selecting any other segment. I have 15 million rows data hence request for dynamic measures.
- I have tried my best to explain the situation. Sorry for any bad grammer or spelling mistake.
Regards
Harish
P.S. - I tried to use your link but it not working. Also in my excel link there a sheet called "Criteria". you can also go through there.
- 6 years ago
Hi,
You may download my Excel solution workbook from here. I have written DAX measures to solve the problem. This can very easily be imported into PowerBI Desktop but before you do so, please check the results thoroughly.
Hope this helps.
- 6 years ago
Hi,
You may download my Excel solution workbook from here. I have written DAX measures to solve the problem. This can very easily be imported into PowerBI Desktop but before you do so, please check the results thoroughly.
Hope this helps.
Hi Ashish_Mathur , Many Many Thanks... Thats what I wanted... You are my superhero.... Bravo Bravo Bravo.
Regards
Harish Rathore
- Ashish_Mathur6 years agoSuper User
- Ashish_Mathur6 years agoSuper User
You are welcome. Thank you for yoru kind words.
- HarishRathore6 years agoHelper IIHi Ashish_Mathur, I have one query. When I am removing "Town Name" from Row labels in pivot then I am not getting "Town Classification" anymore. I have 124 towns in my original data and I want to show summary of town classification. For example what is the market share in town classification, number of towns in each town class. Basically I want to use town classification in row labels. Can you please help me????
Regards
Harish Rathore - Ashish_Mathur6 years agoSuper User
Hi,
This is a tough one to solve because a measure cannot be used as a slicer/filter or in row/column labels. However, i think i have a solution. Please see the image below and let me know if this is what you are expecting.
- HarishRathore6 years agoHelper IIHi Ashish_Mathur, I want something like this but can we remove town names whenever we want? Or town names have to be there? I have 124 towns which would fall under Stronghold, Headroom, Emerging and small. So sometimes I will have to use only summary of town classification.
Regards - Ashish_Mathur6 years agoSuper User
Hi,
Yes, you absolutely can. You may now drag the "Classification of Town" field anywhere - row labels/column labels or slicers. Here are the screenshots. You may also remove Town names from the Pivot Table completely.
Is this exactly what you want?
- HarishRathore6 years agoHelper IIAshish_Mathur, yeah. That's what exactly I wanted. Can you please share the file and the process?
Regards - Ashish_Mathur6 years agoSuper User
Will do so in a couple of days.
- HarishRathore6 years agoHelper IIOk.
- HarishRathore6 years agoHelper IIThanks a lot Ashish_Mathur. Million Kudos to You.
- Ashish_Mathur6 years agoSuper User
You are welcome.