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

PL-300日本語 real exams

Exam Code: PL-300J

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

Updated: Aug 15, 2026

Q & A: 515 Questions and Answers

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  • 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.

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

  • 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.

  • 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.

Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

  • Visualize and analyze the data (25-30%)
  • Deploy and maintain assets (20-25%)
  • Model the data (30-35%)
  • Prepare the data (15-20%)

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

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