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

  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Aug 31, 2026     Q & A: 472 Questions and Answers

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About Microsoft PL-300日本語 Exam

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

Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

  • Time Duration: 180 minutes

  • Number of Questions: 40-60 questions

  • The passing score: 700

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%- Load and configure data
  • 1. Integrate data from multiple sources
    • 2. Configure data refresh settings
      • 3. Define table structures and properties
        - Profile and clean data
        • 1. Manage data types, columns, and rows
          • 2. Resolve inconsistencies, null values, and errors
            • 3. Evaluate data statistics and column properties
              • 4. Transform data using Power Query Editor
                - 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 2: Model the data25-30%- Optimize model performance
                        • 1. Reduce cardinality and data size
                          • 2. Optimize relationships and calculations
                            • 3. Use aggregations and composite models
                              - 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
                                      - Create model calculations
                                      • 1. Use DAX: calculated columns, calculated tables, measures
                                        • 2. Use CALCULATE and filter context
                                          • 3. Implement aggregation and time intelligence
                                            Topic 3: Visualize and analyze data25-30%- Perform data analysis
                                            • 1. Create and manage bookmarks and tooltips
                                              • 2. Implement custom visuals and R/Python scripts
                                                • 3. Interpret results and identify trends
                                                  - Enhance reports with analytics
                                                  • 1. Apply conditional formatting and custom visuals
                                                    • 2. Create paginated reports
                                                      • 3. Use AI visuals, forecasts, and key influencers
                                                        - Create reports and dashboards
                                                        • 1. Choose appropriate visualizations
                                                          • 2. Create dashboards and pinned elements
                                                            • 3. Apply filters, slicers, and drill-through
                                                              • 4. Design report layout, formatting, and interactivity
                                                                Topic 4: 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. Publish, update, and organize reports/datasets
                                                                          • 3. Create and configure workspaces
                                                                            - 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

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