Microsoft PL-300 Korean real exam prep : 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: Aug 09, 2026
  • Q&As: 515 Questions and Answers

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Microsoft PL-300 Korean Value Pack (Frequently Bought Together)

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PL-300 Korean exam dumps

What are the special features of the Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Understanding business context, including organizational strategy and objectives

  • Identifying sources of data that can contribute to achieving business goals

  • Developing dashboards that provide actionable insights into business performance

  • Creating custom data models that support analysis and reporting requirements

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

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

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

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Skills measured

  • Visualize and analyze the data (25-30%)
  • Model the data (30-35%)
  • Deploy and maintain assets (20-25%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
  • Prepare the data (15-20%)

Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize and analyze data25-30%- 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. Create dashboards and pinned elements
          • 2. Choose appropriate visualizations
            • 3. Apply filters, slicers, and drill-through
              • 4. Design report layout, formatting, and interactivity
                - Perform data analysis
                • 1. Interpret results and identify trends
                  • 2. Create and manage bookmarks and tooltips
                    • 3. Implement custom visuals and R/Python scripts
                      Topic 2: Manage and secure Power BI15-20%- 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. Manage data refresh and scheduled updates
                              • 2. Publish, update, and organize reports/datasets
                                • 3. Create and configure workspaces
                                  - 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
                                        Topic 3: Prepare the data25-30%- Profile and clean data
                                        • 1. Transform data using Power Query Editor
                                          • 2. Resolve inconsistencies, null values, and errors
                                            • 3. Manage data types, columns, and rows
                                              • 4. Evaluate data statistics and column properties
                                                - 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. 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
                                                              Topic 4: Model the data25-30%- Design data models
                                                              • 1. Implement role-playing dimensions
                                                                • 2. Create relationships: cardinality, cross-filter direction, security
                                                                  • 3. Create common date tables
                                                                    • 4. Define tables, columns, and hierarchies
                                                                      - Optimize model performance
                                                                      • 1. Optimize relationships and calculations
                                                                        • 2. Reduce cardinality and data size
                                                                          • 3. Use aggregations and composite models
                                                                            - Create model calculations
                                                                            • 1. Implement aggregation and time intelligence
                                                                              • 2. Use DAX: calculated columns, calculated tables, measures
                                                                                • 3. Use CALCULATE and filter context

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