Once you've built and opened your model in Power BI Desktop, here are recommended enhancements:
The tool auto-generates a record count and URL link measure on your fact table. Build on those with your own business metrics:
Total Revenue = SUM(Orders[Amount])
Average Order Value = DIVIDE([Total Revenue], [Order Count])
Win Rate = DIVIDE(
COUNTROWS(FILTER(Opportunities, Opportunities[Status] = "Won")),
COUNTROWS(Opportunities)
)
Create drill-down paths in your dimension tables:
- Date: Year → Quarter → Month → Week → Day
- Geography: Country → State/Province → City
- Organization: Business Unit → Team → Owner
By default, this utility follows the best practice of hiding columns that end users don't need:
- GUID/ID columns (like
accountid) - They are kept in the model for relationships, but hidden from report view
- For lookup fields, use sub-column controls (ID/Name/Type/Yomi) to keep only what report authors need
- If you find that you have additional values that are only needed for formulas, you can hide them as well.
Add a report page that shows:
- Your data model diagram
- Key measure definitions
- Data refresh information
- Known limitations
If using Import, Dual (All), or Dual (Select) storage modes, implement RLS to control data access:
- Go to Modeling → Manage roles
- Create roles that filter data based on user context
- Assign users to roles in Power BI Service
Once you publish your report to Power BI Service:
- This ensures each user sees only their permitted data
- Required for Dataverse row-level security to work
- Enables view filters based on current user context
- See the Publishing and Deployment section for detailed steps
- Configure scheduled refresh (up to 8 times per day)
- Set up failure notifications
- Consider implementing Power BI RLS if needed (see step 6)