Microsoft PL-300 dumps - in .pdf

PL-300 pdf
  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst
  • Updated: Oct 03, 2026
  • Q & A: 472 Questions and Answers
  • PDF Price: $59.99

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  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst
  • Updated: Oct 03, 2026
  • Q & A: 472 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft PL-300 dumps - Testing Engine

PL-300 Testing Engine
  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst
  • Updated: Oct 03, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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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

Microsoft Power BI Data Analyst Exam Certification Details:

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

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

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 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.

  • 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.

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

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