Microsoft PL-300 Deutsch Q&A - in .pdf

  • PL-300 Deutsch pdf
  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 01, 2026
  • Q & A: 515 Questions and Answers
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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
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  • Updated: Aug 01, 2026
  • Q & A: 515 Questions and Answers
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Microsoft PL-300 Deutsch Q&A - Testing Engine

  • PL-300 Deutsch Testing Engine
  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 01, 2026
  • Q & A: 515 Questions and Answers
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Microsoft Power BI Data Analyst Exam Certification Details:

Sample QuestionsMicrosoft Power BI Data Analyst Sample Questions
Schedule ExamPearson VUE
Exam CodePL-300
Books / TrainingCourse PL-300T00: Microsoft Power BI Data Analyst
Duration180 mins
Number of Questions40-60
Exam NameMicrosoft Certified - Power BI Data Analyst Associate
Passing Score700 / 1000
Exam Price$165 (USD)

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

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The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Model the data25-30%- Design data models
  • 1. Define tables, columns, and hierarchies
    • 2. Implement role-playing dimensions
      • 3. Create relationships: cardinality, cross-filter direction, security
        • 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. Implement aggregation and time intelligence
                  • 2. Use DAX: calculated columns, calculated tables, measures
                    • 3. Use CALCULATE and filter context
                      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
                            - Enhance reports with analytics
                            • 1. Use AI visuals, forecasts, and key influencers
                              • 2. Apply conditional formatting and custom visuals
                                • 3. Create paginated reports
                                  - Create reports and dashboards
                                  • 1. Create dashboards and pinned elements
                                    • 2. Apply filters, slicers, and drill-through
                                      • 3. Design report layout, formatting, and interactivity
                                        • 4. Choose appropriate visualizations
                                          Prepare the data25-30%- Load and configure data
                                          • 1. Define table structures and properties
                                            • 2. Configure data refresh settings
                                              • 3. Integrate data from multiple sources
                                                - 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
                                                        - Get or connect to data
                                                        • 1. Identify and connect to data sources or shared semantic models
                                                          • 2. Create and modify parameters
                                                            • 3. Configure data source settings, credentials, and privacy levels
                                                              • 4. Choose storage modes: Import, DirectQuery, DirectLake
                                                                Manage and secure Power BI15-20%- Deploy and distribute content
                                                                • 1. Share reports, dashboards, and apps
                                                                  • 2. Embed content in applications or websites
                                                                    • 3. Monitor usage and performance
                                                                      - 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. Publish, update, and organize reports/datasets
                                                                              • 2. Manage data refresh and scheduled updates
                                                                                • 3. Create and configure workspaces
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