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

  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Aug 22, 2026
  • Q & A: 472 Questions and Answers

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About Microsoft PL-300 Korean Exam

Skills measured

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

For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

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

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Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

  • You have at least one year of experience using Power BI Desktop.

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

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Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Analyze the Data10-15%- Work with metrics in Power BI
  • 1. Define and monitor KPIs
  • 2. Track goals with scorecards
  • 3. Create metrics using Microsoft measurements
  • 4. Use the Decomposition Tree visual
- Perform analysis in Power BI
  • 1. Generate Pinn visual insights
  • 2. Identify patterns and trends
  • 3. Configure auto-insights
  • 4. Use the Q&A visual
  • 5. Apply Quick Insights
Topic 2: Model the Data25-30%- Optimize model performance
  • 1. Validate performance and resolve issues
  • 2. Configure aggregations
  • 3. Optimize Dax queries
  • 4. Optimize DirectQuery models
  • 5. Improve user experience by hiding objects
- Design a data model
  • 1. Design a star schema or snowflake schema
  • 2. Implement row-level security
  • 3. Resolve performance issues with relationships
  • 4. Apply field metadata and groupings
  • 5. Determine the appropriate granularity
  • 6. Define tables and table schemas
- Create measures and DAX calculations
  • 1. Write and use basic DAX syntax
  • 2. Create semi-additive measures
  • 3. Use CALCULATE and FILTER functions
  • 4. Create calculated measures
  • 5. Use Time Intelligence functions
  • 6. Implement context transition
- Develop the data model
  • 1. Create common date tables
  • 2. Create calculated tables and columns
  • 3. Use the calculation group feature
  • 4. Build hierarchies and hierarchical fields
  • 5. Implement row-level security roles
  • 6. Configure table relationships
Topic 3: Visualize the Data25-30%- Enrich reports with advanced visuals
  • 1. Integrate Microsoft Copilot for Power BI
  • 2. Use dynamic page navigation
  • 3. Create custom visuals
  • 4. Configure R and Python visuals
- Build visuals
  • 1. Configure data colors and shapes
  • 2. Determine the appropriate visual type
  • 3. Configure visual interactions and cross-filtering
  • 4. Apply AI insights and enhanced analytics
  • 5. Apply sorting and filtering to visuals
  • 6. Format and configure pages and report backgrounds
- Enhance reports for user experience
  • 1. Apply artistic formatting to visuals
  • 2. Add tooltips and navigation
  • 3. Add accessibility features and compliance
  • 4. Design for mobile and specific layouts
Topic 4: Prepare the Data10-15%- Clean, transform, and load the data
  • 1. Profile the data
  • 2. Configure data loading and queries
  • 3. Identify the data structure
  • 4. Resolve data quality issues
  • 5. Apply user-friendly naming conventions to columns and tables
  • 6. Design and build intermediate tables
  • 7. Determine proper data types
- Get data from various data sources
  • 1. Identify and connect to a data source
  • 2. Use Microsoft Fabric and OneLake
  • 3. Select a shared dataset or create a local copy
  • 4. Choose between DirectQuery, Import, and Dual storage modes
  • 5. Configure dataset refresh
  • 6. Change data source settings
Topic 5: Manage and Maintain Workspace Items10-15%- Create and manage workspaces
  • 1. Configure content certification
  • 2. Publish and update a Power BI app
  • 3. Configure workspace membership and roles
  • 4. Endorse sensitive content with sensitivity labels
- Manage datasets
  • 1. Manage gateways and data sources
  • 2. Resolve dataset permission issues
  • 3. Configure dataset metadata and properties
  • 4. Manage dataset refresh scheduling

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