Microsoft PL-300日本語 dumps - in .pdf

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: Aug 22, 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: Aug 22, 2026
  • Q & A: 472 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
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PL-300日本語 Testing Engine
  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Aug 22, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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Microsoft PL-300 exam, also known as the Microsoft Power BI Data Analyst, is a certification exam that is designed to test a candidate's ability to use Power BI to analyze and visualize data. PL-300J exam is intended for individuals who have experience using Power BI and want to validate their skills and knowledge in this area. Passing PL-300J exam demonstrates competency in using Power BI to create and deliver data insights.

Microsoft PL-300 exam, also known as the Microsoft Power BI Data Analyst exam, is a certification test designed for professionals who work with data analytics and business intelligence. Microsoft Power BI Data Analyst (PL-300日本語版) certification validates the skills and knowledge required to design and build data models, create reports and visualizations, and manage data sources with Microsoft Power BI. PL-300J exam is intended for individuals who are responsible for analyzing data and creating insights to support business decisions.

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Microsoft Power BI Data Analyst Certification Exam Reference

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

Microsoft PL-300日本語 Exam Syllabus Topics:

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

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