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PL-300日本語 pdf
  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 472 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 472 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
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  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

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

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