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

  • Exam Code: PL-300-KR
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Jul 19, 2026
  • Q & A: 515 Questions and Answers

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About Microsoft PL-300 Korean Exam Questions

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

  • The passing score: 700

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

  • Time Duration: 180 minutes

  • Number of Questions: 40-60 questions

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:

  • Creating custom data models that support analysis and reporting requirements

  • Developing dashboards that provide actionable insights into business performance

  • Understanding business context, including organizational strategy and objectives

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

Skills measured

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

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Microsoft PL-300 Korean Exam Syllabus Topics:

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

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