Learn with Microsoft : PL-300 training material for 100% pass

Last Updated: Sep 16, 2026

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Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

  • You have at least one year of experience using Power BI Desktop.

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

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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:

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

  • Developing dashboards that provide actionable insights into business performance

  • Creating custom data models that support analysis and reporting requirements

  • Understanding business context, including organizational strategy and objectives

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

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Microsoft PL-300 Exam Syllabus Topics:

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

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