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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Sep 14, 2026
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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

Retirement date: none

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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  • Then you need to select your preferred payment method which includes credit card or PayPal account etc., and you will receive an email confirmation after successful payment using your credit card or PayPal account etc.

  • Go to the official website of Microsoft, and click on “Microsoft Learning”.

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Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

  • You have at least one year of experience using Power BI Desktop.

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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