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

"Microsoft Power BI Data Analyst (PL-300日本語版)", also known as PL-300 exam, is a Microsoft Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 472 Q&As to your PL-300 Exam preparation. In the PL-300 exam resources, you will cover every field and category in Microsoft Certified: Power BI Data Analyst Associate Certification helping to ready you for your successful Microsoft Certification.

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  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Certification Provider: Microsoft
  • Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate
  • Updated: Aug 22, 2026
  • No. of Questions: 472 Questions & Answers with Testing Engine
  • Download Limit: Unlimited
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The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT

The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.

There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at PrepPDF our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.

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.

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

Microsoft PL-300日本語 Exam Syllabus Topics:

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

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