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

PL-300 Korean real exams

Exam Code: PL-300-KR

Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)

Updated: Aug 10, 2026

Q & A: 515 Questions and Answers

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About Microsoft PL-300 Korean Exam

Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

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

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:

  • Developing dashboards that provide actionable insights into business performance

  • Understanding business context, including organizational strategy and objectives

  • Creating custom data models that support analysis and reporting requirements

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

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

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