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

  • 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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Microsoft PL-300 certification exam is intended for individuals who have a strong background in data analysis and are familiar with the concepts of data modeling, data visualization, and data manipulation. PL-300-Deutsch exam evaluates the knowledge of candidates in designing and building Power BI solutions, creating reports and dashboards, and managing the Power BI service.

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Achieving the Microsoft PL-300 certification demonstrates that a candidate has a deep understanding of the Power BI platform and can use it to provide valuable insights to their organization. Microsoft Power BI Data Analyst (PL-300 Deutsch Version) certification is recognized worldwide and is highly respected in the industry. It can open up new career opportunities and help professionals advance in their current roles. With the Microsoft PL-300 certification, candidates can show employers that they have the skills and knowledge to drive data-driven decision making and make a meaningful impact on their organization.

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
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. 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. Apply data sensitivity labels and protection
                  • 3. Manage permissions and access
                    Visualize and analyze data25-30%- 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
                            - Perform data analysis
                            • 1. Implement custom visuals and R/Python scripts
                              • 2. Create and manage bookmarks and tooltips
                                • 3. Interpret results and identify trends
                                  - Enhance reports with analytics
                                  • 1. Use AI visuals, forecasts, and key influencers
                                    • 2. Apply conditional formatting and custom visuals
                                      • 3. Create paginated reports
                                        Prepare the data25-30%- Load and configure data
                                        • 1. Configure data refresh settings
                                          • 2. Integrate data from multiple sources
                                            • 3. Define table structures and properties
                                              - 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. Manage data types, columns, and rows
                                                        • 2. Evaluate data statistics and column properties
                                                          • 3. Resolve inconsistencies, null values, and errors
                                                            • 4. Transform data using Power Query Editor
                                                              Model the data25-30%- Design data models
                                                              • 1. Create common date tables
                                                                • 2. Define tables, columns, and hierarchies
                                                                  • 3. Implement role-playing dimensions
                                                                    • 4. Create relationships: cardinality, cross-filter direction, security
                                                                      - Create model calculations
                                                                      • 1. Use CALCULATE and filter context
                                                                        • 2. Use DAX: calculated columns, calculated tables, measures
                                                                          • 3. Implement aggregation and time intelligence
                                                                            - Optimize model performance
                                                                            • 1. Use aggregations and composite models
                                                                              • 2. Optimize relationships and calculations
                                                                                • 3. Reduce cardinality and data size

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