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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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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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