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Microsoft Copilot
Microsoft Copilot 2 min

Microsoft Copilot in Power BI: natural language questions to your model

João Barros 27 de August de 2024 2 min read

Microsoft Copilot in Power BI integrates generative AI directly into the service, letting you build reports, write DAX and generate narrative summaries just by describing what you want in natural language.

Requirements

  • Power BI Premium license (P1+) or Fabric capacity F64+.
  • The tenant admin must enable Copilot in Admin Portal → Tenant Settings.
  • Semantic model published in a workspace with Copilot capacity.

Create visuals with natural language

In Power BI Desktop or Service, open the Copilot pane (ribbon button) and write:

User: "Show the monthly sales evolution by product category
       for the last 12 months, with a trend line"

Copilot → automatically generates:
  - Visual: Line and Clustered Column Chart
  - X axis: date hierarchy (Month-Year)
  - Legend: Product Category
  - Line: Trend (DAX: LINESTX)
  - Filter: last 12 months (DATESINPERIOD)

Automatic smart narrative

User: "Create an executive summary of 2024 sales with
       the top 3 insights and comparison with 2023"

Copilot generates a dynamic paragraph with:
  - Total 2024 sales vs 2023
  - Growth % calculated in DAX
  - Automatic outlier identification
  - Conditional formatting by performance

Generate DAX measures

User: "Create a DAX measure to calculate year-over-year
       sales growth as a percentage"

Copilot suggests:
YoY Growth % =
VAR CurrentSales = [Total Sales]
VAR PriorSales = CALCULATE([Total Sales], SAMEPERIODLASTYEAR('Dates'[Date]))
RETURN DIVIDE(CurrentSales - PriorSales, PriorSales)

Tips for better results

  • Use descriptive field names in the model — Copilot relies on them to infer intent.
  • Mark the date table as a Date Table so Copilot understands temporality.
  • Be specific: "sales in € for the last 12 months" is better than "sales evolution".

Conclusion

Copilot in Power BI democratizes report creation, letting business users build analyses without knowledge of DAX or modeling. For analysts, it speeds up prototyping and writing complex measures.

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