Microsoft PL-300日本語 valid dump torrent : Microsoft Power BI Data Analyst (PL-300日本語版)

  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Sep 10, 2026
  • Q&As: 472 Questions and Answers

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Microsoft PL-300 (Microsoft Power BI Data Analyst) certification exam is designed to test the skills of professionals who work with Microsoft Power BI, a business analytics service that allows users to analyze data and share insights. PL-300J exam is intended for individuals who have experience with Power BI and want to prove their expertise in the tool. Microsoft Power BI Data Analyst (PL-300日本語版) certification exam is part of the Microsoft Certified: Power Platform Functional Consultant Associate certification, which demonstrates a professional's ability to work with Power Apps, Power Automate, and Power Virtual Agents.

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Microsoft PL-300 certification exam is an excellent way for data analysts to showcase their skills and knowledge in Power BI. By passing the exam, individuals can demonstrate their proficiency in creating and managing data models, visualizing data, creating reports and dashboards, and managing data sources. Microsoft Power BI Data Analyst (PL-300日本語版) certification can help data analysts advance their careers and increase their earning potential.

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

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Microsoft PL-300 exam is ideal for data analysts who want to build their skills in working with Microsoft Power BI. PL-300J exam focuses on advanced techniques and features such as data modeling, report authoring, and dashboard creation. Microsoft Power BI Data Analyst (PL-300日本語版) certification is a great way to validate your skills and demonstrate your expertise in the field of data analysis.

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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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