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

  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 22, 2026
  • Q & A: 472 Questions and Answers
  • PDF Price: $69.99
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Microsoft PL-300 Deutsch Q&A - Testing Engine

  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 22, 2026
  • Q & A: 472 Questions and Answers
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About Microsoft Power BI Data Analyst (PL-300 Deutsch Version) - PL-300 Deutsch Exam Actual Tests

Microsoft PL-300 certification is a valuable credential for professionals who work with Power BI. It demonstrates that they have the skills and knowledge necessary to work with the platform and that they are able to use it to create meaningful insights for their organizations. It is an excellent way to validate your expertise and differentiate yourself in a competitive job market.

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Microsoft PL-300 exam is designed to test a candidate's knowledge and skills in using Power BI to create data models, reports, and dashboards. PL-300-Deutsch exam covers various topics such as data preparation, data modeling, data visualization, and data analysis. It also tests a candidate's ability to connect to various data sources, import data, and transform data using Power Query.

Microsoft PL-300: Microsoft Power BI Data Analyst is a certification exam that is designed to test and validate the skills of candidates in using Microsoft Power BI to create and manage business intelligence reports and dashboards. PL-300-Deutsch exam is intended for data analysts who work with data from multiple sources and need to create reports and dashboards for business stakeholders. PL-300-Deutsch exam also tests the candidate's ability to work with data models, data preparation, and data visualization.

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
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
        - 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 common date tables
                • 2. Implement role-playing dimensions
                  • 3. Create relationships: cardinality, cross-filter direction, security
                    • 4. Define tables, columns, and hierarchies
                      Prepare the data25-30%- Get or connect to data
                      • 1. Identify and connect to data sources or shared semantic models
                        • 2. Choose storage modes: Import, DirectQuery, DirectLake
                          • 3. Create and modify parameters
                            • 4. Configure data source settings, credentials, and privacy levels
                              - Profile and clean data
                              • 1. Manage data types, columns, and rows
                                • 2. Evaluate data statistics and column properties
                                  • 3. Transform data using Power Query Editor
                                    • 4. Resolve inconsistencies, null values, and errors
                                      - Load and configure data
                                      • 1. Define table structures and properties
                                        • 2. Configure data refresh settings
                                          • 3. Integrate data from multiple sources
                                            Visualize and analyze data25-30%- Create reports and dashboards
                                            • 1. Choose appropriate visualizations
                                              • 2. Create dashboards and pinned elements
                                                • 3. Design report layout, formatting, and interactivity
                                                  • 4. Apply filters, slicers, and drill-through
                                                    - Enhance reports with analytics
                                                    • 1. Apply conditional formatting and custom visuals
                                                      • 2. Create paginated reports
                                                        • 3. Use AI visuals, forecasts, and key influencers
                                                          - Perform data analysis
                                                          • 1. Create and manage bookmarks and tooltips
                                                            • 2. Interpret results and identify trends
                                                              • 3. Implement custom visuals and R/Python scripts
                                                                Manage and secure Power BI15-20%- Manage workspaces and assets
                                                                • 1. Manage data refresh and scheduled updates
                                                                  • 2. Create and configure workspaces
                                                                    • 3. Publish, update, and organize reports/datasets
                                                                      - 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

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