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

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

Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Model the data25-30%- Design data models
  • 1. Implement role-playing dimensions
    • 2. Define tables, columns, and hierarchies
      • 3. Create common date tables
        • 4. Create relationships: cardinality, cross-filter direction, security
          - 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. Use aggregations and composite models
                    • 3. Optimize relationships and calculations
                      Prepare the data25-30%- Load and configure data
                      • 1. Configure data refresh settings
                        • 2. Integrate data from multiple sources
                          • 3. Define table structures and properties
                            - Get or connect to data
                            • 1. Identify and connect to data sources or shared semantic models
                              • 2. Create and modify parameters
                                • 3. Choose storage modes: Import, DirectQuery, DirectLake
                                  • 4. Configure data source settings, credentials, and privacy levels
                                    - 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
                                            Manage and secure Power BI15-20%- Manage workspaces and assets
                                            • 1. Manage data refresh and scheduled updates
                                              • 2. Create and configure workspaces
                                                • 3. Publish, update, and organize reports/datasets
                                                  - 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. Configure row-level security (RLS) and object-level security
                                                            • 3. Manage permissions and access
                                                              Visualize and analyze data25-30%- Perform data analysis
                                                              • 1. Interpret results and identify trends
                                                                • 2. Create and manage bookmarks and tooltips
                                                                  • 3. Implement custom visuals and R/Python scripts
                                                                    - Enhance reports with analytics
                                                                    • 1. Create paginated reports
                                                                      • 2. Use AI visuals, forecasts, and key influencers
                                                                        • 3. Apply conditional formatting and custom visuals
                                                                          - Create reports and dashboards
                                                                          • 1. Design report layout, formatting, and interactivity
                                                                            • 2. Apply filters, slicers, and drill-through
                                                                              • 3. Choose appropriate visualizations
                                                                                • 4. Create dashboards and pinned elements

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