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

PL-300日本語 real exams

Exam Code: PL-300J

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

Updated: Aug 26, 2026

Q & A: 472 Questions and Answers

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About Microsoft PL-300日本語 Exam

Introduction of Microsoft PL-300 Exam

Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.

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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.

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%- Create and manage workspaces
  • 1. Endorse sensitive content with sensitivity labels
  • 2. Publish and update a Power BI app
  • 3. Configure content certification
  • 4. Configure workspace membership and roles
- 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. Use the Decomposition Tree visual
  • 4. Create metrics using Microsoft measurements
- Perform analysis in Power BI
  • 1. Generate Pinn visual insights
  • 2. Use the Q&A visual
  • 3. Apply Quick Insights
  • 4. Configure auto-insights
  • 5. Identify patterns and trends
Topic 3: 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. 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
- Develop the data model
  • 1. Implement row-level security roles
  • 2. Configure table relationships
  • 3. Create common date tables
  • 4. Build hierarchies and hierarchical fields
  • 5. Create calculated tables and columns
  • 6. Use the calculation group feature
- Create measures and DAX calculations
  • 1. Create semi-additive measures
  • 2. Use CALCULATE and FILTER functions
  • 3. Create calculated measures
  • 4. Use Time Intelligence functions
  • 5. Implement context transition
  • 6. Write and use basic DAX syntax
Topic 4: Visualize the Data25-30%- Build visuals
  • 1. Apply AI insights and enhanced analytics
  • 2. Format and configure pages and report backgrounds
  • 3. Determine the appropriate visual type
  • 4. Configure visual interactions and cross-filtering
  • 5. Apply sorting and filtering to visuals
  • 6. Configure data colors and shapes
- Enhance reports for user experience
  • 1. Add tooltips and navigation
  • 2. Design for mobile and specific layouts
  • 3. Add accessibility features and compliance
  • 4. Apply artistic formatting to visuals
- Enrich reports with advanced visuals
  • 1. Integrate Microsoft Copilot for Power BI
  • 2. Create custom visuals
  • 3. Use dynamic page navigation
  • 4. Configure R and Python visuals
Topic 5: Prepare the Data10-15%- 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. Use Microsoft Fabric and OneLake
  • 6. Identify and connect to a data source
- Clean, transform, and load the data
  • 1. Design and build intermediate tables
  • 2. Apply user-friendly naming conventions to columns and tables
  • 3. Profile the data
  • 4. Identify the data structure
  • 5. Configure data loading and queries
  • 6. Determine proper data types
  • 7. Resolve data quality issues

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