Try and practice the latest Microsoft : PL-300 Korean real questions & answers

Last Updated: Aug 13, 2026

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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

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

Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

  • Time Duration: 180 minutes

  • The passing score: 700

  • Number of Questions: 40-60 questions

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Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

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Microsoft PL-300 Korean Exam Syllabus Topics:

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