Power BI is turning 10! Tune in for a special live episode on July 24 with behind-the-scenes stories, product evolution highlights, and a sneak peek at what’s in store for the future.
Save the dateJoin us for an expert-led overview of the tools and concepts you'll need to become a Certified Power BI Data Analyst and pass exam PL-300. Register now.
I'm building a new dataset and struggling with which date method to use.
I want to be able to use slicers to filter any of the three dates that will be used in the report, and I have a few date groupings that are specific to the separate date types (manufacture date, Availability date, Expiry Date).
This leads me to think separate date tables may be the simplest method.
However, it occurred to me that this would make it challenging (impossible?) to create a view of a measure over different date types (example below, because my words are not working well)
Units manufactured | Units Expired | |
Jan | 1'200 | 500 |
Feb | 2'000 | 1'800 |
Mar | 1'300 | 200 |
The only method i can think of to achieve both outcomes is to create the seperate date dimensions and then have a master date table connecting all three - snowflake style. Is there something i'm missing here? is there a simpler/better way?
Solved! Go to Solution.
Hi @Dvayro
Another option is to "generate" a table with dynamic measures.
I created a file with the example.
You can download it from This link
If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.
Hi @Dvayro
Another option is to "generate" a table with dynamic measures.
I created a file with the example.
You can download it from This link
If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.
Check out the July 2025 Power BI update to learn about new features.
This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.
User | Count |
---|---|
60 | |
58 | |
56 | |
38 | |
28 |
User | Count |
---|---|
82 | |
61 | |
45 | |
41 | |
39 |