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Skills measured

  • Visualize and analyze the data (25-30%)
  • Deploy and maintain assets (20-25%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
  • Prepare the data (15-20%)
  • Model the data (30-35%)

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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:

  • 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.

  • 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.

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

  • 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.

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For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

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: 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. Create dashboards and pinned elements
          • 2. Choose appropriate visualizations
            • 3. Apply filters, slicers, and drill-through
              • 4. Design report layout, formatting, and interactivity
                - Enhance reports with analytics
                • 1. Use AI visuals, forecasts, and key influencers
                  • 2. Apply conditional formatting and custom visuals
                    • 3. Create paginated reports
                      Topic 2: Model the data25-30%- Design data models
                      • 1. Create common date tables
                        • 2. Implement role-playing dimensions
                          • 3. Create relationships: cardinality, cross-filter direction, security
                            • 4. Define tables, columns, and hierarchies
                              - Optimize model performance
                              • 1. Use aggregations and composite models
                                • 2. Optimize relationships and calculations
                                  • 3. Reduce cardinality and data size
                                    - Create model calculations
                                    • 1. Implement aggregation and time intelligence
                                      • 2. Use CALCULATE and filter context
                                        • 3. Use DAX: calculated columns, calculated tables, measures
                                          Topic 3: Prepare the data25-30%- Load and configure data
                                          • 1. Integrate data from multiple sources
                                            • 2. Configure data refresh settings
                                              • 3. Define table structures and properties
                                                - Get or connect to data
                                                • 1. Create and modify parameters
                                                  • 2. Choose storage modes: Import, DirectQuery, DirectLake
                                                    • 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. Manage data types, columns, and rows
                                                            • 3. Resolve inconsistencies, null values, and errors
                                                              • 4. Transform data using Power Query Editor
                                                                Topic 4: 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
                                                                      - 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
                                                                            - Deploy and distribute content
                                                                            • 1. Share reports, dashboards, and apps
                                                                              • 2. Embed content in applications or websites
                                                                                • 3. Monitor usage and performance

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