Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!To celebrate FabCon Vienna, we are offering 50% off select exams. Ends October 3rd. Request your discount now.
Hello,
I'm dealing with standard invoice data: invoice number, date, price per unit, cost per unit, quantity, salesperson, shipping destination (city, state, ZIP), etc.
What is the advantage to splitting that data into fact and dimension tables?
Thank you.
Solved! Go to Solution.
Generally, a star schema will give you better performance.
Here is some additional info:
https://www.sqlbi.com/articles/the-importance-of-star-schemas-in-power-bi/
https://www.youtube.com/watch?v=vZndrBBPiQc
Below is the advantacge
1. Identify the Key Dimensaions and its details and move those to Dim tables
2. Have the FActs in offcourse in Fact tables so that those can be aggregated in lower level and used accoridngly joining to Dim table
3. Separting the data in Facts and dimensions are nothing but normalizing it to avoid performance issues
Generally, a star schema will give you better performance.
Here is some additional info:
https://www.sqlbi.com/articles/the-importance-of-star-schemas-in-power-bi/
https://www.youtube.com/watch?v=vZndrBBPiQc
After my post, I read on the forum someone describe the fact/dim tables as: facts are values you want to filter by and dims are values you want to summarize.
Somehow that made a lot of sense.
Thanks for the links.
Yes, I agree with that. You're welcome and happy data modelling 😀