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Updated: Jul 30, 2026

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Microsoft Power BI Data Analyst Certification Exam Reference

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 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.

  • 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.

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

Solutions

Microsoft Power BI Data Analyst Certification Exam is one of the most popular certification exams in the market. However, most candidates don't pass it on their first attempt. The reasons for this are many, but the most common ones are not having enough time to prepare, not knowing where to start and what to study, or not having access to quality learning materials. To help you overcome these obstacles and pass Microsoft Power BI Data Analyst Certification Exam easily, our experts have created a comprehensive Microsoft PL-300 Dumps that will give you everything you need to know to pass Microsoft Power BI Data Analyst Certification Exam quickly and efficiently.

This study guide contains everything you will need to have a deep understanding of this certification and take it with confidence. Our experts have taken great care in creating this study guide by using only high-quality resources available on the internet. Our goal is to help you understand each concept so that when taking the exam, there will be no surprises that throw off your momentum or cause you any stress during your preparation or while taking the exam itself.

Microsoft PL-300日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Power BI Data Analyst
Exam Number:PL-300
Exam Price:$165.00 USD
Certificate Validity Period:1 year
Passing Score:700 (scaled score, passing not publicly disclosed)
Exam Duration:120 minutes
Related Certifications:Microsoft Certified: Power BI Data Analyst Associate
Exam Format:Multiple choice, Case study, Drag and drop, Short answer
Available Languages:English, Japanese, Chinese (Simplified), Korean
Real Exam Qty:40-60
Sample Questions:Microsoft PL-300日本語 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/

Microsoft PL-300日本語 Exam Syllabus Topics:

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

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