Microsoft PL-300-Deutsch exam dumps : Microsoft Power BI Data Analyst (PL-300 Deutsch Version)

  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 29, 2026     Q & A: 472 Questions and Answers

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About Microsoft PL-300 Deutsch Exam

Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • The passing score: 700

  • Time Duration: 180 minutes

  • Number of Questions: 40-60 questions

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

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Schedule exam

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.

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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