Microsoft PL-300 Korean Valid Test : Microsoft Power BI Data Analyst (PL-300 Korean Version)

  • Exam Code: PL-300-KR
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 12, 2026
  • Q&As: 472 Questions and Answers

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Microsoft PL-300 exam is a valuable certification for professionals who work in data analysis and business intelligence. Microsoft Power BI Data Analyst (PL-300 Korean Version) certification demonstrates that the candidate has the skills and knowledge required to design and build effective data models, create compelling reports and visualizations, and manage data sources using Microsoft Power BI. By earning this certification, candidates can enhance their career prospects and demonstrate their expertise to potential employers.

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

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The PL-300 certification exam consists of 40-60 multiple-choice questions, and candidates have two hours to complete the exam. To pass the exam, candidates must score at least 700 out of 1000 points. PL-300-KR exam is available in multiple languages, including English, French, German, Japanese, Korean, Portuguese, and Spanish.

Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model the data25-30%- Design data models
  • 1. Implement role-playing dimensions
    • 2. Create common date tables
      • 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. Use DAX: calculated columns, calculated tables, measures
                  • 2. Implement aggregation and time intelligence
                    • 3. Use CALCULATE and filter context
                      Topic 2: Manage and secure Power BI15-20%- 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
                            - Manage workspaces and assets
                            • 1. Manage data refresh and scheduled updates
                              • 2. Publish, update, and organize reports/datasets
                                • 3. Create and configure workspaces
                                  - Deploy and distribute content
                                  • 1. Share reports, dashboards, and apps
                                    • 2. Embed content in applications or websites
                                      • 3. Monitor usage and performance
                                        Topic 3: Visualize and analyze data25-30%- 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. Create dashboards and pinned elements
                                                • 2. Apply filters, slicers, and drill-through
                                                  • 3. Choose appropriate visualizations
                                                    • 4. Design report layout, formatting, and interactivity
                                                      - Perform data analysis
                                                      • 1. Interpret results and identify trends
                                                        • 2. Implement custom visuals and R/Python scripts
                                                          • 3. Create and manage bookmarks and tooltips
                                                            Topic 4: Prepare the data25-30%- Profile and clean data
                                                            • 1. Evaluate data statistics and column properties
                                                              • 2. Transform data using Power Query Editor
                                                                • 3. Resolve inconsistencies, null values, and errors
                                                                  • 4. Manage data types, columns, and rows
                                                                    - Load and configure data
                                                                    • 1. Configure data refresh settings
                                                                      • 2. Define table structures and properties
                                                                        • 3. Integrate data from multiple sources
                                                                          - Get or connect to data
                                                                          • 1. Create and modify parameters
                                                                            • 2. Configure data source settings, credentials, and privacy levels
                                                                              • 3. Choose storage modes: Import, DirectQuery, DirectLake
                                                                                • 4. Identify and connect to data sources or shared semantic models

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