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Microsoft PL-300J guide torrent - Microsoft Power BI Data Analyst (PL-300日本語版)

Updated: Jul 23, 2026

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PL-300日本語 guide torrent
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)

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

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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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