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Microsoft PL-300 exam is designed for individuals who are interested in becoming a Microsoft Power BI Data Analyst. Microsoft Power BI Data Analyst (PL-300日本語版) certification is aimed at professionals who want to demonstrate their expertise in using Power BI to analyze data and create visualizations. PL-300J exam focuses on various topics, such as data modeling, data visualization, and report authoring.

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

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