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

  • PL-300 Korean pdf
  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Jul 22, 2026
  • Q & A: 515 Questions and Answers
  • Convenient, easy to study.
    Printable Microsoft PL-300-KR PDF Format. It is an electronic file format regardless of the operating system platform.
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  • PDF Price: $69.98

Microsoft PL-300 Korean Value Pack
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  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
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  • Updated: Jul 22, 2026
  • Q & A: 515 Questions and Answers
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Microsoft PL-300 Korean Q&A - Testing Engine

  • PL-300 Korean Testing Engine
  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Jul 22, 2026
  • Q & A: 515 Questions and Answers
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What is the salary of the Microsoft Power BI Data Analyst Certified professional

The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:

  • Canada; CAD 70,000

  • United States; USD 90,000

  • India; INR 500,000

  • United Kingdom; POUNDS 60,000

  • Australia; AUD 75,000

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%)
  • Prepare the data (15-20%)
  • Deploy and maintain assets (20-25%)
  • Model the data (30-35%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
Microsoft PL-300 Korean Exam Syllabus Topics:
SectionWeightObjectives
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. Resolve performance issues with relationships
  • 5. Define tables and table schemas
  • 6. Apply field metadata and groupings
- Develop the data model
  • 1. Implement row-level security roles
  • 2. Create calculated tables and columns
  • 3. Configure table relationships
  • 4. Build hierarchies and hierarchical fields
  • 5. Create common date tables
  • 6. Use the calculation group feature
- Optimize model performance
  • 1. Validate performance and resolve issues
  • 2. Configure aggregations
  • 3. Optimize Dax queries
  • 4. Improve user experience by hiding objects
  • 5. Optimize DirectQuery models
- Create measures and DAX calculations
  • 1. Use Time Intelligence functions
  • 2. Write and use basic DAX syntax
  • 3. Use CALCULATE and FILTER functions
  • 4. Create semi-additive measures
  • 5. Create calculated measures
  • 6. Implement context transition
Manage and Maintain Workspace Items10-15%- Create and manage workspaces
  • 1. Endorse sensitive content with sensitivity labels
  • 2. Configure content certification
  • 3. Configure workspace membership and roles
  • 4. Publish and update a Power BI app
- Manage datasets
  • 1. Manage gateways and data sources
  • 2. Resolve dataset permission issues
  • 3. Configure dataset metadata and properties
  • 4. Manage dataset refresh scheduling
Analyze the Data10-15%- Perform analysis in Power BI
  • 1. Use the Q&A visual
  • 2. Generate Pinn visual insights
  • 3. Configure auto-insights
  • 4. Apply Quick Insights
  • 5. Identify patterns and trends
- Work with metrics in Power BI
  • 1. Define and monitor KPIs
  • 2. Create metrics using Microsoft measurements
  • 3. Track goals with scorecards
  • 4. Use the Decomposition Tree visual
Visualize the Data25-30%- Enhance reports for user experience
  • 1. Design for mobile and specific layouts
  • 2. Apply artistic formatting to visuals
  • 3. Add accessibility features and compliance
  • 4. Add tooltips and navigation
- 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. Format and configure pages and report backgrounds
  • 2. Determine the appropriate visual type
  • 3. Apply AI insights and enhanced analytics
  • 4. Configure visual interactions and cross-filtering
  • 5. Configure data colors and shapes
  • 6. Apply sorting and filtering to visuals
Prepare the Data10-15%- Get data from various data sources
  • 1. Use Microsoft Fabric and OneLake
  • 2. Select a shared dataset or create a local copy
  • 3. Configure dataset refresh
  • 4. Choose between DirectQuery, Import, and Dual storage modes
  • 5. Identify and connect to a data source
  • 6. Change data source settings
- Clean, transform, and load the data
  • 1. Identify the data structure
  • 2. Configure data loading and queries
  • 3. Resolve data quality issues
  • 4. Profile the data
  • 5. Apply user-friendly naming conventions to columns and tables
  • 6. Determine proper data types
  • 7. Design and build intermediate tables
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