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

PL-300 Deutsch testking pdf

Exam Code: PL-300-Deutsch

Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)

Updated: Jul 26, 2026

Q & A: 515 Questions and Answers

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About Microsoft Power BI Data Analyst (PL-300 Deutsch Version) : PL-300 Deutsch Exam

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  • Australia; AUD 75,000

  • India; INR 500,000

  • United States; USD 90,000

  • Canada; CAD 70,000

  • United Kingdom; POUNDS 60,000

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

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

  • Number of Questions: 40-60 questions

  • Time Duration: 180 minutes

  • The passing score: 700

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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