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

PL-300 Deutsch Exam Questions
  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 515 Questions and Answers
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About Microsoft PL-300 Deutsch Exam Braindumps

Microsoft Power BI Data Analyst certification is a valuable certification for professionals who work with data and aspire to improve their skills in data analysis and business intelligence. The Microsoft PL-300 exam is designed to test and validate your skills in creating and managing business intelligence reports and dashboards using Microsoft Power BI. Passing PL-300-Deutsch exam can help you advance your career and demonstrate your expertise in this field.

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Microsoft PL-300 exam is designed with the latest technology and tools, providing candidates with a comprehensive understanding of Power BI. PL-300-Deutsch exam covers important topics such as data visualization, data modeling, data preparation, and data analysis. PL-300-Deutsch exam also includes questions on how to use Power BI to create reports and dashboards that are optimized for mobile devices and web browsers.

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

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