Microsoft PL-300日本語 exam : Microsoft Power BI Data Analyst (PL-300日本語版)

PL-300日本語 Exam Simulator
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Aug 08, 2026
  • Q & A: 515 Questions and Answers

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Microsoft PL-300日本語 exam simulator

Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

  • Model the data (30-35%)
  • Visualize and analyze the data (25-30%)
  • Prepare the data (15-20%)
  • Deploy and maintain assets (20-25%)

For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

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

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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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