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

  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 06, 2026
  • Q & A: 515 Questions and Answers

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

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Microsoft Power BI Data Analyst Certification Exam Reference

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What are the special features of the Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Creating custom data models that support analysis and reporting requirements

  • Developing dashboards that provide actionable insights into business performance

  • Identifying sources of data that can contribute to achieving business goals

  • Understanding business context, including organizational strategy and objectives

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What are the steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam

The steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam are as follows:

  • The next step is to fill out your personal information such as name, email address, country and state city etc., which is mandatory to complete your registration process successfully.

  • You will see a list of courses that are available on this website. Select “Microsoft Power BI Data Analyst Certification Exam” and click on “Enroll Now” button.

  • 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”.

  • After successful registration process, you will receive an email confirmation from Microsoft with all the details about your course including access code etc., which will be sent to your registered email ID provided during registration process.

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Manage and secure Power BI15-20%- Deploy and distribute content
  • 1. Monitor usage and performance
    • 2. Share reports, dashboards, and apps
      • 3. Embed content in applications or websites
        - Manage workspaces and assets
        • 1. Publish, update, and organize reports/datasets
          • 2. Manage data refresh and scheduled updates
            • 3. Create and configure workspaces
              - Implement security and governance
              • 1. Apply data sensitivity labels and protection
                • 2. Configure row-level security (RLS) and object-level security
                  • 3. Manage permissions and access
                    Prepare the data25-30%- Profile and clean data
                    • 1. Transform data using Power Query Editor
                      • 2. Evaluate data statistics and column properties
                        • 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. Configure data refresh settings
                                • 3. Integrate data from multiple sources
                                  - Get or connect to data
                                  • 1. Configure data source settings, credentials, and privacy levels
                                    • 2. Choose storage modes: Import, DirectQuery, DirectLake
                                      • 3. Identify and connect to data sources or shared semantic models
                                        • 4. Create and modify parameters
                                          Visualize and analyze data25-30%- Create reports and dashboards
                                          • 1. Create dashboards and pinned elements
                                            • 2. Choose appropriate visualizations
                                              • 3. Design report layout, formatting, and interactivity
                                                • 4. Apply filters, slicers, and drill-through
                                                  - Enhance reports with analytics
                                                  • 1. Use AI visuals, forecasts, and key influencers
                                                    • 2. Create paginated reports
                                                      • 3. Apply conditional formatting and custom visuals
                                                        - Perform data analysis
                                                        • 1. Create and manage bookmarks and tooltips
                                                          • 2. Implement custom visuals and R/Python scripts
                                                            • 3. Interpret results and identify trends
                                                              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
                                                                    - 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

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