Microsoft PL-300 Korean Exam Questions : 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 02, 2026
  • Q&As: 472 Questions and Answers

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

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There are many IT certifications available in the market today, but if you are looking for a job as a data analyst then you should give this certification a chance. This certification will help you to stand out from the crowd and get hired easily by many companies. Microsoft Power BI Data Analyst Certification Exam is the most valuable certification program for IT professionals in their respective fields. Microsoft PL-300 Dumps is a must-have certificate for all IT professionals who want to pursue their career in the field of data analytics.

The Microsoft Power BI Data Analyst Certification Exam is a certification exam that will help you to demonstrate your expertise in using the Microsoft Power BI platform. This exam tests the candidate's ability to analyze data with Power BI and create reports that are accurate, insightful and easy to read. Once you pass this exam, you will receive a certificate that shows your competence in performing these tasks. The certificate is valid for three years, so if you want to keep your skills up-to-date then you should take additional training during this time period.

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Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Visualize and analyze data25-30%- Create reports and dashboards
  • 1. Design report layout, formatting, and interactivity
    • 2. Apply filters, slicers, and drill-through
      • 3. Create dashboards and pinned elements
        • 4. Choose appropriate visualizations
          - 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
                      Model the data25-30%- Design data models
                      • 1. Create common date tables
                        • 2. Define tables, columns, and hierarchies
                          • 3. Create relationships: cardinality, cross-filter direction, security
                            • 4. Implement role-playing dimensions
                              - Create model calculations
                              • 1. Implement aggregation and time intelligence
                                • 2. Use DAX: calculated columns, calculated tables, measures
                                  • 3. Use CALCULATE and filter context
                                    - Optimize model performance
                                    • 1. Optimize relationships and calculations
                                      • 2. Use aggregations and composite models
                                        • 3. Reduce cardinality and data size
                                          Prepare the data25-30%- Get or connect to data
                                          • 1. Create and modify parameters
                                            • 2. Identify and connect to data sources or shared semantic models
                                              • 3. Configure data source settings, credentials, and privacy levels
                                                • 4. Choose storage modes: Import, DirectQuery, DirectLake
                                                  - 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. Transform data using Power Query Editor
                                                          • 2. Resolve inconsistencies, null values, and errors
                                                            • 3. Evaluate data statistics and column properties
                                                              • 4. Manage data types, columns, and rows
                                                                Manage and secure Power BI15-20%- Deploy and distribute content
                                                                • 1. Monitor usage and performance
                                                                  • 2. Share reports, dashboards, and apps
                                                                    • 3. Embed content in applications or websites
                                                                      - Manage workspaces and assets
                                                                      • 1. Create and configure workspaces
                                                                        • 2. Manage data refresh and scheduled updates
                                                                          • 3. Publish, update, and organize reports/datasets
                                                                            - Implement security and governance
                                                                            • 1. Manage permissions and access
                                                                              • 2. Apply data sensitivity labels and protection
                                                                                • 3. Configure row-level security (RLS) and object-level security

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