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

  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Oct 01, 2026
  • Q&As: 472 Questions and Answers

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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.

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Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

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

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