Exam Code: PL-300
Exam Name: Microsoft Power BI Data Analyst
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate

Try Microsoft : PL-300 valid & accurate questions and answers

PL-300

Last Updated: Aug 21, 2026

No. of Questions: 472 Questions & Answers with Testing Engine

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Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • The passing score: 700

  • Number of Questions: 40-60 questions

  • Time Duration: 180 minutes

  • Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

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Skills measured

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

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

Microsoft PL-300 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model the data25-30%- Design data models
  • 1. Create relationships: cardinality, cross-filter direction, security
    • 2. Define tables, columns, and hierarchies
      • 3. Create common date tables
        • 4. Implement role-playing dimensions
          - Create model calculations
          • 1. Use DAX: calculated columns, calculated tables, measures
            • 2. Use CALCULATE and filter context
              • 3. Implement aggregation and time intelligence
                - Optimize model performance
                • 1. Use aggregations and composite models
                  • 2. Optimize relationships and calculations
                    • 3. Reduce cardinality and data size
                      Topic 2: 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. Evaluate data statistics and column properties
                              • 2. Manage data types, columns, and rows
                                • 3. Transform data using Power Query Editor
                                  • 4. Resolve inconsistencies, null values, and errors
                                    - 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
                                            Topic 3: Manage and secure Power BI15-20%- Manage workspaces and assets
                                            • 1. Publish, update, and organize reports/datasets
                                              • 2. Create and configure workspaces
                                                • 3. Manage data refresh and scheduled updates
                                                  - 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. Apply data sensitivity labels and protection
                                                          • 2. Manage permissions and access
                                                            • 3. Configure row-level security (RLS) and object-level security
                                                              Topic 4: 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. Apply conditional formatting and custom visuals
                                                                          • 3. Create paginated reports
                                                                            - Perform data analysis
                                                                            • 1. Implement custom visuals and R/Python scripts
                                                                              • 2. Create and manage bookmarks and tooltips
                                                                                • 3. Interpret results and identify trends

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