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Last Updated: Jul 24, 2026

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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:

  • 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.

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

  • 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.

  • 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.

  • 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.

Microsoft Power BI Data Analyst Exam Certification Details:

Number of Questions40-60
Passing Score700 / 1000
Exam NameMicrosoft Certified - Power BI Data Analyst Associate
Books / TrainingCourse PL-300T00: Microsoft Power BI Data Analyst
Schedule ExamPearson VUE
Exam CodePL-300
Duration180 mins
Sample QuestionsMicrosoft Power BI Data Analyst Sample Questions
Exam Price$165 (USD)

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

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Microsoft PL-300 Exam Syllabus Topics:

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