The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredCompete to become Power BI Data Viz World Champion! First round ends August 18th. Get started.
I have data that gets loaded monthly. Each month is a snapshot of all active customers. My goal is to compare the most recent snapshot to the same period last year so I can categorize customers. Here is a sample of a scaled down dataset.
I was able to calculate a table that categorizes each customer and then used measures to count each category. The issue is that this approach is not dynamic.
The pbix file attached has my attempt to make the table dynamic. My [YoY Cust Categories] is essentially my calculated table in measure form. I don’t think this approach will work. It is very slow and when I use it in my scaled-up data set I get a memory error.
Any other approach will greatly appreciate.
Data: https://drive.google.com/file/d/1ZbipUeq7psvY9m0_wk55Az7BVWOKp9TU/view?usp=sharing
PBIX: https://drive.google.com/file/d/1Xpei1D6KqRALHcFGKKDWNVj_xJFCdE_X/view?usp=sharing
Solved! Go to Solution.
Hi @nbs333
Here's how to perform such an analysis properly: Calculate New, Returning, Lost, and Recovered Customers in #dax - SQLBI
Hi @nbs333
Here's how to perform such an analysis properly: Calculate New, Returning, Lost, and Recovered Customers in #dax - SQLBI
User | Count |
---|---|
26 | |
10 | |
8 | |
6 | |
6 |
User | Count |
---|---|
32 | |
14 | |
11 | |
10 | |
9 |