Power BI is turning 10, and we’re marking the occasion with a special community challenge. Use your creativity to tell a story, uncover trends, or highlight something unexpected.
Get startedJoin 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.
Hello,
I am getting more and more confused after more than one week of research on what would be the best schema for the attached report. This doesn't seem like a typical star schema with fact and dim tables (even though I named them like that).
Background:
I want to understand which employees can work with which customers. This will allow me to better understand where I have skill gaps from the skills and regions perspective.
Each employee has a skill assigned and each customer has a PMV type assigned. There is also a mapping table showing which PMVs can be covered by which skills.
Data:
fact Employees - list of employees, their skills and cities where they are based
fact Customers - list of customers, their pmvs and cities where they are based
dim Skills - mapping of _SkillKey with the Skill name
dim Regions - mapping of _RegionKey with Region name
dim PMV Skill Mapping - mapping allowing to understand which skills can cover which pmvs (and other way round)
dim PMV - mapping of _PMVKey and PMV Type
dim MasterMap - table appended in PQ to get an ultimate view of all the locations (customers & cities)
Ideally I would like to understand things like:
A) where are based customers/employees with certain skill/pmv (selected from the filter)
B) what is the ratio (# of customers per engineer) for each skill/pmv
My biggest struggle is how to design a data model that will help to answer these questions... when I get it to work for A) it will not work for B) and another way round..
Any feedback is much appreciated!
thanks!
Hi @Anonymous ,
Please provide some data and expected output.
Best Regards
Community Support Team _ Polly
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
You're spot on. Power BI is not OLAP. You can emulate some of the features with inactive relationships, USERELATIONSHIP() and/or CROSSFILTER() but you may also want to explore using separate data models for these separate business questions. Or go back to SSAS 🙂
This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.
Check out the June 2025 Power BI update to learn about new features.
User | Count |
---|---|
73 | |
71 | |
54 | |
38 | |
31 |
User | Count |
---|---|
71 | |
64 | |
62 | |
50 | |
46 |