Exam Code: PL-300
Exam Name: Microsoft Power BI Data Analyst
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate

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PL-300

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Updated: Jul 31, 2026

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Microsoft PL-300 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Power BI Data Analyst
Exam Number:PL-300
Available Languages:English, Japanese, Chinese (Simplified), Korean
Certificate Validity Period:1 year
Passing Score:700 (scaled score, passing not publicly disclosed)
Exam Duration:120 minutes
Real Exam Qty:40-60
Related Certifications:Microsoft Certified: Power BI Data Analyst Associate
Exam Format:Multiple choice, Case study, Drag and drop, Short answer
Exam Price:$165.00 USD
Sample Questions:Microsoft PL-300 Sample Questions
Exam Way:Online proctored exam (Pearson VUE) or in-person testing center
Pre Condition:No mandatory prerequisites, but Microsoft recommends having foundational knowledge of data concepts and Microsoft Power BI before taking the exam.
Official Syllabus URL:https://learn.microsoft.com/en-us/certifications/exams/pl-300/

The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT

The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.

There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at Easy4Engine our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.

Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

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

Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

  • Visualize and analyze the data (25-30%)
  • Prepare the data (15-20%)
  • Model the data (30-35%)
  • Deploy and maintain assets (20-25%)

Microsoft PL-300 Exam Syllabus Topics:

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

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