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I have a table called Sales Transactions loaded to my report. That is the fact table and there's a few dimension tables (Product Name, Location, Date) pointing to it.
On my fact table, I have some main columns:
order_id - identifies the ID of the transaction. It is not unique, because if there were X products being bought on a transaction, then there will be X lines, one for each product, and they will all have the same order_id value.
sales_units - the number of units sold for a specific product on a specific transaction.
sku_code - the code of the products being bought sales_units - number of times the product was bought.
So let's say I bought 2 units of the same product and 1 unit of a different one. Here's how the transaction would get to my table:
order_id | sku_number | sales_units |
4354325 | ABC | 1 |
4354325 | XYZ | 2 |
Based on that, I would like to understand the average units per transaction. In theory, it's a very simple calculation: SUM of sales_units / DISTINCT COUNT of order_ids.
However, what if I want to analyse the average UPT for product ABC?
I would then need to SUM all the sales_units from the order_ids that contained ABC (not just ABC sales_units), and divide by the distinct count of these order_ids.
Anyone knows how can I do it through DAX?
Solved! Go to Solution.
Based on the information you have offered, you can refer to the folloing measure
Sample data
Then create a mesure
Measure = var a=SUMMARIZE(FILTER(ALLSELECTED('Table'),[sku_number]="ABC"),[order_id])
var b=SUMX(FILTER(ALLSELECTED('Table'),[order_id] in a),[sales_units])
return DIVIDE(b,COUNTROWS(a))
Output
Best Regards!
Yolo Zhu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Based on the information you have offered, you can refer to the folloing measure
Sample data
Then create a mesure
Measure = var a=SUMMARIZE(FILTER(ALLSELECTED('Table'),[sku_number]="ABC"),[order_id])
var b=SUMX(FILTER(ALLSELECTED('Table'),[order_id] in a),[sales_units])
return DIVIDE(b,COUNTROWS(a))
Output
Best Regards!
Yolo Zhu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
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