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Updated: Jul 24, 2026

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Microsoft PL-300 Deutsch Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Power BI Data Analyst
Exam Number:PL-300
Passing Score:700 (out of 1000)
Available Languages:English, Japanese, Chinese (Simplified), Chinese (Traditional), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Italian, Indonesian
Certificate Validity Period:12 months
Exam Duration:180 minutes
Real Exam Qty:40-60
Exam Price:USD 165
Related Certifications:Microsoft Certified: Data Analyst Associate
Microsoft Certified: Power Platform Associate
Exam Format:Multiple choice (single/multiple response), Drag and drop, Performance-based, Case studies, Simulation
Recommended Training:Microsoft Official Course: PL-300T00
Microsoft Learn - PL-300 Learning Path
Exam Registration:Pearson VUE Registration
Microsoft Learn - Schedule Exam
Sample Questions:Microsoft PL-300 Deutsch Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:No mandatory prerequisites; recommended experience: proficiency in Power Query, DAX, data profiling, and understanding of data security concepts
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300

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

  • Number of Questions: 40-60 questions

  • The passing score: 700

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

  • Time Duration: 180 minutes

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

Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

  • Deploy and maintain assets (20-25%)
  • Visualize and analyze the data (25-30%)
  • Prepare the data (15-20%)
  • Model the data (30-35%)

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- Manage workspaces and assets
  • 1. Publish, update, and organize reports/datasets
    • 2. Create and configure workspaces
      • 3. Manage data refresh and scheduled updates
        - Implement security and governance
        • 1. Manage permissions and access
          • 2. Apply data sensitivity labels and protection
            • 3. Configure row-level security (RLS) and object-level security
              - Deploy and distribute content
              • 1. Embed content in applications or websites
                • 2. Monitor usage and performance
                  • 3. Share reports, dashboards, and apps
                    Topic 2: Model the data25-30%- Create model calculations
                    • 1. Implement aggregation and time intelligence
                      • 2. Use CALCULATE and filter context
                        • 3. Use DAX: calculated columns, calculated tables, measures
                          - Design data models
                          • 1. Create relationships: cardinality, cross-filter direction, security
                            • 2. Implement role-playing dimensions
                              • 3. Create common date tables
                                • 4. Define tables, columns, and hierarchies
                                  - Optimize model performance
                                  • 1. Use aggregations and composite models
                                    • 2. Reduce cardinality and data size
                                      • 3. Optimize relationships and calculations
                                        Topic 3: Prepare the data25-30%- Load and configure data
                                        • 1. Integrate data from multiple sources
                                          • 2. Define table structures and properties
                                            • 3. Configure data refresh settings
                                              - 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
                                                      - Profile and clean data
                                                      • 1. Resolve inconsistencies, null values, and errors
                                                        • 2. Manage data types, columns, and rows
                                                          • 3. Evaluate data statistics and column properties
                                                            • 4. Transform data using Power Query Editor
                                                              Topic 4: Visualize and analyze data25-30%- Create reports and dashboards
                                                              • 1. Create dashboards and pinned elements
                                                                • 2. Choose appropriate visualizations
                                                                  • 3. Apply filters, slicers, and drill-through
                                                                    • 4. Design report layout, formatting, and interactivity
                                                                      - 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

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