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

Microsoft PL-300日本語 exam
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Oct 01, 2026
  • Q & A: 472 Questions and Answers
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Skills measured
  • Visualize and analyze the data (25-30%)
  • Prepare the data (15-20%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
  • Deploy and maintain assets (20-25%)
  • Model the data (30-35%)

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

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

  • India; INR 500,000

  • United States; USD 90,000

  • Australia; AUD 75,000

  • United Kingdom; POUNDS 60,000

What is the exam cost of the Microsoft Power BI Data Analyst Certification Exam

The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

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

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