Microsoft Power BI Data Analyst : PL-300

  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst
  • Updated: Sep 28, 2026     Q & A: 472 Questions and Answers

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What are the steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam

The steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam are as follows:

  • Go to the official website of Microsoft, and click on “Microsoft Learning”.

  • The next step is to fill out your personal information such as name, email address, country and state city etc., which is mandatory to complete your registration process successfully.

  • You will see a list of courses that are available on this website. Select “Microsoft Power BI Data Analyst Certification Exam” and click on “Enroll Now” button.

  • Then you need to select your preferred payment method which includes credit card or PayPal account etc., and you will receive an email confirmation after successful payment using your credit card or PayPal account etc.

  • After successful registration process, you will receive an email confirmation from Microsoft with all the details about your course including access code etc., which will be sent to your registered email ID provided during registration process.

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

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.

Microsoft PL-300 Exam Syllabus Topics:

SectionWeightObjectives
Model the data25-30%- Optimize model performance
  • 1. Reduce cardinality and data size
    • 2. Use aggregations and composite models
      • 3. Optimize relationships and calculations
        - Create model calculations
        • 1. Use DAX: calculated columns, calculated tables, measures
          • 2. Implement aggregation and time intelligence
            • 3. Use CALCULATE and filter context
              - Design data models
              • 1. Define tables, columns, and hierarchies
                • 2. Create relationships: cardinality, cross-filter direction, security
                  • 3. Implement role-playing dimensions
                    • 4. Create common date tables
                      Visualize and analyze data25-30%- Perform data analysis
                      • 1. Create and manage bookmarks and tooltips
                        • 2. Interpret results and identify trends
                          • 3. Implement custom visuals and R/Python scripts
                            - Create reports and dashboards
                            • 1. Apply filters, slicers, and drill-through
                              • 2. Design report layout, formatting, and interactivity
                                • 3. Choose appropriate visualizations
                                  • 4. Create dashboards and pinned elements
                                    - Enhance reports with analytics
                                    • 1. Use AI visuals, forecasts, and key influencers
                                      • 2. Apply conditional formatting and custom visuals
                                        • 3. Create paginated reports
                                          Manage and secure Power BI15-20%- Implement security and governance
                                          • 1. Manage permissions and access
                                            • 2. Configure row-level security (RLS) and object-level security
                                              • 3. Apply data sensitivity labels and protection
                                                - Manage workspaces and assets
                                                • 1. Create and configure workspaces
                                                  • 2. Manage data refresh and scheduled updates
                                                    • 3. Publish, update, and organize reports/datasets
                                                      - Deploy and distribute content
                                                      • 1. Share reports, dashboards, and apps
                                                        • 2. Monitor usage and performance
                                                          • 3. Embed content in applications or websites
                                                            Prepare the data25-30%- Profile and clean data
                                                            • 1. Evaluate data statistics and column properties
                                                              • 2. Transform data using Power Query Editor
                                                                • 3. Manage data types, columns, and rows
                                                                  • 4. Resolve inconsistencies, null values, and errors
                                                                    - Get or connect to data
                                                                    • 1. Create and modify parameters
                                                                      • 2. Choose storage modes: Import, DirectQuery, DirectLake
                                                                        • 3. Identify and connect to data sources or shared semantic models
                                                                          • 4. Configure data source settings, credentials, and privacy levels
                                                                            - Load and configure data
                                                                            • 1. Define table structures and properties
                                                                              • 2. Configure data refresh settings
                                                                                • 3. Integrate data from multiple sources

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