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Exam Code: PL-300
Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate
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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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Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

  • Deploy and maintain assets (20-25%)
  • Model the data (30-35%)
  • Prepare the data (15-20%)
  • Visualize and analyze the data (25-30%)

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Introduction of Microsoft PL-300 Exam

Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the data25-30%- Get or connect to data
  • 1. Identify and connect to data sources or shared semantic models
    • 2. Configure data source settings, credentials, and privacy levels
      • 3. Choose storage modes: Import, DirectQuery, DirectLake
        • 4. Create and modify parameters
          - Load and configure data
          • 1. Integrate data from multiple sources
            • 2. Define table structures and properties
              • 3. Configure data refresh settings
                - Profile and clean data
                • 1. Transform data using Power Query Editor
                  • 2. Manage data types, columns, and rows
                    • 3. Evaluate data statistics and column properties
                      • 4. Resolve inconsistencies, null values, and errors
                        Topic 2: Model the data25-30%- Create model calculations
                        • 1. Use DAX: calculated columns, calculated tables, measures
                          • 2. Use CALCULATE and filter context
                            • 3. Implement aggregation and time intelligence
                              - Design data models
                              • 1. Implement role-playing dimensions
                                • 2. Create common date tables
                                  • 3. Define tables, columns, and hierarchies
                                    • 4. Create relationships: cardinality, cross-filter direction, security
                                      - Optimize model performance
                                      • 1. Use aggregations and composite models
                                        • 2. Reduce cardinality and data size
                                          • 3. Optimize relationships and calculations
                                            Topic 3: Manage and secure Power BI15-20%- Deploy and distribute content
                                            • 1. Embed content in applications or websites
                                              • 2. Share reports, dashboards, and apps
                                                • 3. Monitor usage and performance
                                                  - Manage workspaces and assets
                                                  • 1. Manage data refresh and scheduled updates
                                                    • 2. Create and configure workspaces
                                                      • 3. Publish, update, and organize reports/datasets
                                                        - Implement security and governance
                                                        • 1. Apply data sensitivity labels and protection
                                                          • 2. Manage permissions and access
                                                            • 3. Configure row-level security (RLS) and object-level security
                                                              Topic 4: Visualize and analyze data25-30%- Perform data analysis
                                                              • 1. Implement custom visuals and R/Python scripts
                                                                • 2. Interpret results and identify trends
                                                                  • 3. Create and manage bookmarks and tooltips
                                                                    - Enhance reports with analytics
                                                                    • 1. Apply conditional formatting and custom visuals
                                                                      • 2. Use AI visuals, forecasts, and key influencers
                                                                        • 3. Create paginated reports
                                                                          - Create reports and dashboards
                                                                          • 1. Design report layout, formatting, and interactivity
                                                                            • 2. Apply filters, slicers, and drill-through
                                                                              • 3. Create dashboards and pinned elements
                                                                                • 4. Choose appropriate visualizations

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