Microsoft PL-300 Exam Questions : Microsoft Power BI Data Analyst

  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst
  • Updated: Oct 10, 2026
  • Q&As: 472 Questions and Answers

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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 PassSureExam 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.

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

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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

What is the salary of the Microsoft Power BI Data Analyst Certified professional

The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:

  • United States; USD 90,000

  • India; INR 500,000

  • Australia; AUD 75,000

  • United Kingdom; POUNDS 60,000

  • Canada; CAD 70,000

Learn more about the exam

The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.

Microsoft PL-300 Exam Syllabus Topics:

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

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