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: 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
  • Value Pack Total: $139.98  $89.99
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Microsoft PL-300日本語 dumps - Testing Engine

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: Sep 14, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

About Microsoft PL-300日本語 Instant Exam Download

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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. ITExamDownload Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.

What are the special features of the Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Understanding business context, including organizational strategy and objectives

  • Creating custom data models that support analysis and reporting requirements

  • Developing dashboards that provide actionable insights into business performance

  • Identifying sources of data that can contribute to achieving business goals

For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

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

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