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shoaibalvi
Helper I
Helper I

How to visualise outliers in gross to net discount percentages in a large dataset.

Hi all,

 

I have a source data that has columns for "distribution channels", "customer groups", "customer names", "product names", "gross price", "net price", and "gross-to-net percentage".

 

Various customers are grouped under customer groups, and various customer groups are hive up into distribution channels. 

 

The hypothesis I want to test / visualise is whether G2N% (gross-to-net percentage) for a given product was comparable across customers / customer groups and or distribution channels, and whether there were any outliers from the average G2N % on a product level. 

 

I am looking for ideas as to how best achieve this. I was thinking of scatter / bubble chart but I am not entirely sure what fields should go in the x and y-axis, and which summarisation should be used to detect outliers (e.g. avg G2N %, median, std. dev etc.?).

 

Just looking for any feedback / tips / suggestions from the community that might help turn on the little light bulb in my head!!

 

Thanks! 

 

 

2 REPLIES 2
TomMartens
Super User
Super User

Hey @shoaibalvi ,

 

consider creating a pbix that contains sample data, but still reflects your data model (tables, relationships, calculated columns, and measures). Upload the pbix to OneDrive, Google Drive, or Dropbox and share the link. If you are using a spreadsheet to create the sample data instead of the manual input method share the spreadsheet file as well.

 

Regards,

Tom



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Hamburg, Germany

Hi @TomMartens 

 

I have uploaded sample data and PBIX here

 

I am struggling to determine what should i really use on my x and y axis, and what summarisation should be used to achieve the desired result

 

Regards,

Shoaib

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