Microsoft PL-300日本語 : Microsoft Power BI Data Analyst (PL-300日本語版)

PL-300日本語 pass collection

Exam Code: PL-300J

Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)

Updated: Jul 29, 2026

Q & A: 515 Questions and Answers

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About Microsoft PL-300日本語 Exam

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Microsoft Power BI Data Analyst Exam Certification Details:

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

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

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Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
Model the data25-30%- Design data models
  • 1. Create common date tables
    • 2. Define tables, columns, and hierarchies
      • 3. Implement role-playing dimensions
        • 4. Create relationships: cardinality, cross-filter direction, security
          - Optimize model performance
          • 1. Use aggregations and composite models
            • 2. Optimize relationships and calculations
              • 3. Reduce cardinality and data size
                - Create model calculations
                • 1. Use DAX: calculated columns, calculated tables, measures
                  • 2. Use CALCULATE and filter context
                    • 3. Implement aggregation and time intelligence
                      Manage and secure Power BI15-20%- 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
                            - Deploy and distribute content
                            • 1. Monitor usage and performance
                              • 2. Share reports, dashboards, and apps
                                • 3. Embed content in applications or websites
                                  - Manage workspaces and assets
                                  • 1. Publish, update, and organize reports/datasets
                                    • 2. Manage data refresh and scheduled updates
                                      • 3. Create and configure workspaces
                                        Visualize and analyze data25-30%- 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. Apply filters, slicers, and drill-through
                                                  • 3. Design report layout, formatting, and interactivity
                                                    • 4. Choose appropriate visualizations
                                                      - Perform data analysis
                                                      • 1. Create and manage bookmarks and tooltips
                                                        • 2. Interpret results and identify trends
                                                          • 3. Implement custom visuals and R/Python scripts
                                                            Prepare the data25-30%- Load and configure data
                                                            • 1. Configure data refresh settings
                                                              • 2. Integrate data from multiple sources
                                                                • 3. Define table structures and properties
                                                                  - 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
                                                                          - Get or connect to data
                                                                          • 1. Create and modify parameters
                                                                            • 2. Identify and connect to data sources or shared semantic models
                                                                              • 3. Choose storage modes: Import, DirectQuery, DirectLake
                                                                                • 4. Configure data source settings, credentials, and privacy levels

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