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

PL-300 Korean Exam Questions
  • Exam Code: PL-300-KR
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Sep 06, 2026
  • Q & A: 472 Questions and Answers
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Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • Time Duration: 180 minutes

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

  • Number of Questions: 40-60 questions

  • The passing score: 700

Is Microsoft Power BI Data Analyst Certification Exam Worth It

There are many IT certifications available in the market today, but if you are looking for a job as a data analyst then you should give this certification a chance. This certification will help you to stand out from the crowd and get hired easily by many companies. Microsoft Power BI Data Analyst Certification Exam is the most valuable certification program for IT professionals in their respective fields. Microsoft PL-300 Dumps is a must-have certificate for all IT professionals who want to pursue their career in the field of data analytics.

The Microsoft Power BI Data Analyst Certification Exam is a certification exam that will help you to demonstrate your expertise in using the Microsoft Power BI platform. This exam tests the candidate's ability to analyze data with Power BI and create reports that are accurate, insightful and easy to read. Once you pass this exam, you will receive a certificate that shows your competence in performing these tasks. The certificate is valid for three years, so if you want to keep your skills up-to-date then you should take additional training during this time period.

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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. RealExamFree 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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Microsoft PL-300 Korean Exam Syllabus Topics:

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

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