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

PL-300日本語 actual test
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Aug 24, 2026
  • Q & A: 472 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $69.99  

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

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

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

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