Microsoft PL-300 Korean Q&A - in .pdf

  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 12, 2026
  • Q & A: 472 Questions and Answers
  • Printable Microsoft PL-300 Korean PDF Format. It is an electronic file format regardless of the operating system platform.
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Microsoft PL-300 Korean Q&A - Testing Engine

  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 12, 2026
  • Q & A: 472 Questions and Answers
  • Install on multiple computers for self-paced, at-your-convenience training.
  • PC Test Engine Price: $69.99
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Skills measured

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

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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

Schedule exam

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

Microsoft PL-300 Korean Exam Syllabus Topics:

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

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