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Hi,
I'm running quite a large data model (around 20 queries), with many of my tables containing multiple date columns.
I am curious how others approach the use of Date Dimension tables in large models. Do you leverage multiple DateDimension tables with relationships to your different date fields, or use one Date Dimension table with multiple relationships?
Currently, I am trying to use one Date Dimension table but with my limited proficency in DAX, the filter contexing proves to complicat things for me.
Here's a photo of the model
Solved! Go to Solution.
I posted something on Transitive Relationships and Date Dimensions that might help:
http://community.powerbi.com/t5/Desktop/Transitive-Relationships/m-p/8574#M1449
You can pragmatically do either way.
Separate Data Tables
PROS
CONS
If your data model size in memory is pretty small, you could use separate tables. I prefer only one Date table, creating multiple relationships to it, and altering the appropriate measures to add the USERELATIONSHIP function to the filter context parameter of the CALCULATE function. Once you get the hang of it, it's not as hard as it first seems.
One advantage of multiple date tables is that you can label the attributes clearly as to what they represent (e.g. Invoice Date, Invoice Month, Order Date, Order Month).
It can also be helpful if you have 2 dates associated with the same fact and want to combine filters. (E.g. all returns in October 2015 that have an original purchase date of 2014).
You can pragmatically do either way.
Separate Data Tables
PROS
CONS
If your data model size in memory is pretty small, you could use separate tables. I prefer only one Date table, creating multiple relationships to it, and altering the appropriate measures to add the USERELATIONSHIP function to the filter context parameter of the CALCULATE function. Once you get the hang of it, it's not as hard as it first seems.
One advantage of multiple date tables is that you can label the attributes clearly as to what they represent (e.g. Invoice Date, Invoice Month, Order Date, Order Month).
It can also be helpful if you have 2 dates associated with the same fact and want to combine filters. (E.g. all returns in October 2015 that have an original purchase date of 2014).
I posted something on Transitive Relationships and Date Dimensions that might help:
http://community.powerbi.com/t5/Desktop/Transitive-Relationships/m-p/8574#M1449
March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount! Early Bird pricing ends December 9th.
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