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

PL-300 Deutsch real exams

Exam Code: PL-300-Deutsch

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

Updated: Sep 11, 2026

Q & A: 472 Questions and Answers

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

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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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No matter how many times you take the Microsoft Power BI Data Analyst Certification Exam, you will never be able to finish it. This is because the exam is designed to be as difficult as possible. When you first sit down and begin answering questions, you may feel like there are a lot of easy ones. This is just part of the test's strategy. they want to make sure that you think everything's going smoothly, so that when they throw in a difficult question later on, it will be much harder for you to answer.

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Microsoft Power BI Data Analyst Certification Exam Reference

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- 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
        - Manage workspaces and assets
        • 1. Publish, update, and organize reports/datasets
          • 2. Create and configure workspaces
            • 3. Manage data refresh and scheduled updates
              - Deploy and distribute content
              • 1. Share reports, dashboards, and apps
                • 2. Embed content in applications or websites
                  • 3. Monitor usage and performance
                    Topic 2: Model the data25-30%- Create model calculations
                    • 1. Implement aggregation and time intelligence
                      • 2. Use DAX: calculated columns, calculated tables, measures
                        • 3. Use CALCULATE and filter context
                          - Optimize model performance
                          • 1. Use aggregations and composite models
                            • 2. Optimize relationships and calculations
                              • 3. Reduce cardinality and data size
                                - 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
                                        Topic 3: Prepare the data25-30%- 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
                                                - 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. Create and modify parameters
                                                      • 4. Choose storage modes: Import, DirectQuery, DirectLake
                                                        - Load and configure data
                                                        • 1. Configure data refresh settings
                                                          • 2. Define table structures and properties
                                                            • 3. Integrate data from multiple sources
                                                              Topic 4: Visualize and analyze data25-30%- Create reports and dashboards
                                                              • 1. Choose appropriate visualizations
                                                                • 2. Apply filters, slicers, and drill-through
                                                                  • 3. Create dashboards and pinned elements
                                                                    • 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. Apply conditional formatting and custom visuals
                                                                              • 2. Use AI visuals, forecasts, and key influencers
                                                                                • 3. Create paginated reports

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