Microsoft PL-300 : Microsoft Power BI Data Analyst

PL-300 real exams

Exam Code: PL-300

Exam Name: Microsoft Power BI Data Analyst

Updated: Aug 11, 2026

Q & A: 515 Questions and Answers

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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

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What is the exam cost of the Microsoft Power BI Data Analyst Certification Exam

The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

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

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Microsoft Power BI Data Analyst Certification Exam Reference

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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.

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Microsoft PL-300 Exam Syllabus Topics:

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

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