Microsoft PL-300 Korean exam - in .pdf

PL-300 Korean pdf
  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • PDF Price: $69.99
  • PDF Demo

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  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft PL-300 Korean exam - Testing Engine

PL-300 Korean Testing Engine
  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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

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Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- 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
        - Deploy and distribute content
        • 1. Embed content in applications or websites
          • 2. Monitor usage and performance
            • 3. Share reports, dashboards, and apps
              - Manage workspaces and assets
              • 1. Publish, update, and organize reports/datasets
                • 2. Manage data refresh and scheduled updates
                  • 3. Create and configure workspaces
                    Topic 2: 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. Apply conditional formatting and custom visuals
                              • 3. Use AI visuals, forecasts, and key influencers
                                - Create reports and dashboards
                                • 1. Apply filters, slicers, and drill-through
                                  • 2. Design report layout, formatting, and interactivity
                                    • 3. Create dashboards and pinned elements
                                      • 4. Choose appropriate visualizations
                                        Topic 3: Model the data25-30%- Create model calculations
                                        • 1. Implement aggregation and time intelligence
                                          • 2. Use CALCULATE and filter context
                                            • 3. Use DAX: calculated columns, calculated tables, measures
                                              - Design data models
                                              • 1. Create common date tables
                                                • 2. Define tables, columns, and hierarchies
                                                  • 3. Implement role-playing dimensions
                                                    • 4. Create relationships: cardinality, cross-filter direction, security
                                                      - Optimize model performance
                                                      • 1. Reduce cardinality and data size
                                                        • 2. Optimize relationships and calculations
                                                          • 3. Use aggregations and composite models
                                                            Topic 4: Prepare the data25-30%- Profile and clean data
                                                            • 1. Transform data using Power Query Editor
                                                              • 2. Manage data types, columns, and rows
                                                                • 3. Resolve inconsistencies, null values, and errors
                                                                  • 4. Evaluate data statistics and column properties
                                                                    - 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. Choose storage modes: Import, DirectQuery, DirectLake
                                                                          • 4. Create and modify parameters
                                                                            - Load and configure data
                                                                            • 1. Integrate data from multiple sources
                                                                              • 2. Define table structures and properties
                                                                                • 3. Configure data refresh settings

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