Hi,
I need some help with this challenge 😊
What do I want?
I need a report with the number of customers with active products for each day.
For example:
Date | A | A,B | B | C | Total |
09-12-2019 | 1 | 2 | 1 | 2 | 6 |
08-12-2019 | 1 | 1 | 1 | 2 | 5 |
Etc. | | | | | |
So on the 9th of December there is 1 customer who has only active product A, there are 2 customers who have active product A and also active product B (ActiveProductPath = A, B), there is 1 customer with only active product B and there are 2 customers who have only active product C.
Dummy file and a solution
You can find a dummy file with a solution! here: https://www.dropbox.com/s/a6eykz0o7g5jdht/ActiveProductPathFinalv2.pbix?dl=0
You have already a solution, so why this question?
The technique used as a solution isn’t working for large datasets because of memory.
Can you explain this?
The dummy file contains 14 products (= rows), with the technique used (day-customer-productpath) this becomes 922 rows (= 65,86 times 14).
I have another file with 7.769 different products and with the technique used in the dummy file the table “day-customer-productpath” became 4.965.732 rows (= x 639,25)! This wasn’t a problem for Power BI.
But now I have a file with 1.7 million different products and with this large dataset my computer gets a memory-problem…….
So what is your question?
Is it possible to solve this challenge without the technique used in the dummy file? With other words, is there a DAX-solution to create virtual tables and to count customers with different “ActiveProductsPaths”?
Hope to hear from you soon.
Thanks in advance!
Regards from the Netherlands,
Cor
