Advance your Data & AI career with 50 days of live learning, dataviz contests, hands-on challenges, study groups & certifications and more!
Get registeredGet Fabric Certified for FREE during Fabric Data Days. Don't miss your chance! Request now
Hi all,
I'm struggling with setting up a data model. I have 6 fact tables with employee metrics and would need to filter/display by Employee attribute (dept, city, level etc.). I have a current Employee Roster with lists all current employees (no dups) with all current attributes. The issue is that the fact tables might have Employees that are NOT on the current roster or have changed levels, depts etc. All of the fact tables have duplicate rows for all employees.
The only way I've been able to solve this is with 14 DIM tables listing out all of my attributes then connecting all of them to each of my fact tables.
Is there a more efficient way to set up is model?
Solved! Go to Solution.
Unless looking at the model, I can not say. But If you are in a star schema. And you have separated out fact and dimension and making sure all common fields are in dimensions. Then it is a good design. I am sure you have taken care of SCD behavior of employee details.
Slowly Changing Dimension.
Means employee's manager and department changes etc. You have also created a current employee fact. Means somewhere you are taking care of that too.
Unless looking at the model, I can not say. But If you are in a star schema. And you have separated out fact and dimension and making sure all common fields are in dimensions. Then it is a good design. I am sure you have taken care of SCD behavior of employee details.
Slowly Changing Dimension.
Means employee's manager and department changes etc. You have also created a current employee fact. Means somewhere you are taking care of that too.
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 97 | |
| 74 | |
| 50 | |
| 47 | |
| 44 |