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: Aug 24, 2026
  • Q & A: 472 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)
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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. PassReview Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.

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

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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

Microsoft PL-300 Korean Exam Syllabus Topics:

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