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Exam Code: PL-300
Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate

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PL-300 Deutsch

Last Updated: Sep 06, 2026

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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize the Data25-30%- Enhance reports for user experience
  • 1. Add accessibility features and compliance
  • 2. Add tooltips and navigation
  • 3. Apply artistic formatting to visuals
  • 4. Design for mobile and specific layouts
- Enrich reports with advanced visuals
  • 1. Create custom visuals
  • 2. Configure R and Python visuals
  • 3. Integrate Microsoft Copilot for Power BI
  • 4. Use dynamic page navigation
- Build visuals
  • 1. Configure visual interactions and cross-filtering
  • 2. Apply AI insights and enhanced analytics
  • 3. Configure data colors and shapes
  • 4. Format and configure pages and report backgrounds
  • 5. Apply sorting and filtering to visuals
  • 6. Determine the appropriate visual type
Topic 2: Manage and Maintain Workspace Items10-15%- Manage datasets
  • 1. Configure dataset metadata and properties
  • 2. Manage gateways and data sources
  • 3. Resolve dataset permission issues
  • 4. Manage dataset refresh scheduling
- Create and manage workspaces
  • 1. Publish and update a Power BI app
  • 2. Configure workspace membership and roles
  • 3. Configure content certification
  • 4. Endorse sensitive content with sensitivity labels
Topic 3: Model the Data25-30%- Create measures and DAX calculations
  • 1. Create semi-additive measures
  • 2. Use Time Intelligence functions
  • 3. Write and use basic DAX syntax
  • 4. Implement context transition
  • 5. Create calculated measures
  • 6. Use CALCULATE and FILTER functions
- Optimize model performance
  • 1. Optimize DirectQuery models
  • 2. Validate performance and resolve issues
  • 3. Configure aggregations
  • 4. Improve user experience by hiding objects
  • 5. Optimize Dax queries
- Design a data model
  • 1. Implement row-level security
  • 2. Apply field metadata and groupings
  • 3. Resolve performance issues with relationships
  • 4. Define tables and table schemas
  • 5. Design a star schema or snowflake schema
  • 6. Determine the appropriate granularity
- Develop the data model
  • 1. Create calculated tables and columns
  • 2. Use the calculation group feature
  • 3. Create common date tables
  • 4. Implement row-level security roles
  • 5. Build hierarchies and hierarchical fields
  • 6. Configure table relationships
Topic 4: Prepare the Data10-15%- Clean, transform, and load the data
  • 1. Determine proper data types
  • 2. Apply user-friendly naming conventions to columns and tables
  • 3. Profile the data
  • 4. Design and build intermediate tables
  • 5. Identify the data structure
  • 6. Configure data loading and queries
  • 7. Resolve data quality issues
- Get data from various data sources
  • 1. Choose between DirectQuery, Import, and Dual storage modes
  • 2. Use Microsoft Fabric and OneLake
  • 3. Change data source settings
  • 4. Identify and connect to a data source
  • 5. Select a shared dataset or create a local copy
  • 6. Configure dataset refresh
Topic 5: Analyze the Data10-15%- Work with metrics in Power BI
  • 1. Track goals with scorecards
  • 2. Create metrics using Microsoft measurements
  • 3. Use the Decomposition Tree visual
  • 4. Define and monitor KPIs
- Perform analysis in Power BI
  • 1. Apply Quick Insights
  • 2. Use the Q&A visual
  • 3. Configure auto-insights
  • 4. Identify patterns and trends
  • 5. Generate Pinn visual insights

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