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

PL-300 Deutsch pass collection

Exam Code: PL-300-Deutsch

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

Updated: Aug 01, 2026

Q & A: 515 Questions and Answers

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About Microsoft PL-300 Deutsch Exam

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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.

For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

Benefits

The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. ExamCost Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.

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

What is the exam cost of the Microsoft Power BI Data Analyst Certification Exam

The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Model the data25-30%- Create model calculations
  • 1. Use DAX: calculated columns, calculated tables, measures
    • 2. Implement aggregation and time intelligence
      • 3. Use CALCULATE and filter context
        - Optimize model performance
        • 1. Reduce cardinality and data size
          • 2. Optimize relationships and calculations
            • 3. Use aggregations and composite models
              - 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
                      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
                            - Manage workspaces and assets
                            • 1. Create and configure workspaces
                              • 2. Publish, update, and organize reports/datasets
                                • 3. Manage data refresh and scheduled updates
                                  - Deploy and distribute content
                                  • 1. Share reports, dashboards, and apps
                                    • 2. Monitor usage and performance
                                      • 3. Embed content in applications or websites
                                        Visualize and analyze data25-30%- Create reports and dashboards
                                        • 1. Design report layout, formatting, and interactivity
                                          • 2. Create dashboards and pinned elements
                                            • 3. Apply filters, slicers, and drill-through
                                              • 4. Choose appropriate visualizations
                                                - Enhance reports with analytics
                                                • 1. Create paginated reports
                                                  • 2. Use AI visuals, forecasts, and key influencers
                                                    • 3. Apply conditional formatting and custom visuals
                                                      - Perform data analysis
                                                      • 1. Interpret results and identify trends
                                                        • 2. Create and manage bookmarks and tooltips
                                                          • 3. Implement custom visuals and R/Python scripts
                                                            Prepare the data25-30%- Load and configure data
                                                            • 1. Configure data refresh settings
                                                              • 2. Define table structures and properties
                                                                • 3. Integrate data from multiple sources
                                                                  - Profile and clean data
                                                                  • 1. Manage data types, columns, and rows
                                                                    • 2. Transform data using Power Query Editor
                                                                      • 3. Resolve inconsistencies, null values, and errors
                                                                        • 4. Evaluate data statistics and column properties
                                                                          - 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

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