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Last Updated: Sep 09, 2026

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

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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Manage and secure Power BI15-20%- Manage workspaces and assets
  • 1. Publish, update, and organize reports/datasets
    • 2. Manage data refresh and scheduled updates
      • 3. Create and configure workspaces
        - Implement security and governance
        • 1. Apply data sensitivity labels and protection
          • 2. Configure row-level security (RLS) and object-level security
            • 3. Manage permissions and access
              - Deploy and distribute content
              • 1. Embed content in applications or websites
                • 2. Monitor usage and performance
                  • 3. Share reports, dashboards, and apps
                    Prepare the data25-30%- Get or connect to data
                    • 1. Create and modify parameters
                      • 2. Configure data source settings, credentials, and privacy levels
                        • 3. Identify and connect to data sources or shared semantic models
                          • 4. Choose storage modes: Import, DirectQuery, DirectLake
                            - Load and configure data
                            • 1. Define table structures and properties
                              • 2. Integrate data from multiple sources
                                • 3. Configure data refresh settings
                                  - Profile and clean data
                                  • 1. Transform data using Power Query Editor
                                    • 2. Resolve inconsistencies, null values, and errors
                                      • 3. Manage data types, columns, and rows
                                        • 4. Evaluate data statistics and column properties
                                          Visualize and analyze data25-30%- Create reports and dashboards
                                          • 1. Design report layout, formatting, and interactivity
                                            • 2. Create dashboards and pinned elements
                                              • 3. Apply filters, slicers, and drill-through
                                                • 4. Choose appropriate visualizations
                                                  - Enhance reports with analytics
                                                  • 1. Use AI visuals, forecasts, and key influencers
                                                    • 2. Apply conditional formatting and custom visuals
                                                      • 3. Create paginated reports
                                                        - Perform data analysis
                                                        • 1. Create and manage bookmarks and tooltips
                                                          • 2. Interpret results and identify trends
                                                            • 3. Implement custom visuals and R/Python scripts
                                                              Model the data25-30%- Design data models
                                                              • 1. Define tables, columns, and hierarchies
                                                                • 2. Create relationships: cardinality, cross-filter direction, security
                                                                  • 3. Implement role-playing dimensions
                                                                    • 4. Create common date tables
                                                                      - Optimize model performance
                                                                      • 1. Use aggregations and composite models
                                                                        • 2. Reduce cardinality and data size
                                                                          • 3. Optimize relationships and calculations
                                                                            - Create model calculations
                                                                            • 1. Use CALCULATE and filter context
                                                                              • 2. Implement aggregation and time intelligence
                                                                                • 3. Use DAX: calculated columns, calculated tables, measures
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