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Microsoft Power BI Data Analyst : PL-300

PL-300

Exam Code: PL-300

Exam Name: Microsoft Power BI Data Analyst

Updated: Aug 21, 2026

Q & A: 472 Questions and Answers

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About Microsoft Power BI Data Analyst certification

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Introduction of Microsoft PL-300 Exam

Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.

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

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Microsoft Power BI Data Analyst Certification Exam Reference

Microsoft PL-300 Exam Syllabus Topics:

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

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