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

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 18, 2026

Q & A: 472 Questions and Answers

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Microsoft Power BI Data Analyst Certification Exam is one of the most popular certification exams in the market. However, most candidates don't pass it on their first attempt. The reasons for this are many, but the most common ones are not having enough time to prepare, not knowing where to start and what to study, or not having access to quality learning materials. To help you overcome these obstacles and pass Microsoft Power BI Data Analyst Certification Exam easily, our experts have created a comprehensive Microsoft PL-300 Dumps that will give you everything you need to know to pass Microsoft Power BI Data Analyst Certification Exam quickly and efficiently.

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

Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

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

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Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
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
          - Get or connect to data
          • 1. Identify and connect to data sources or shared semantic models
            • 2. Configure data source settings, credentials, and privacy levels
              • 3. Create and modify parameters
                • 4. Choose storage modes: Import, DirectQuery, DirectLake
                  - Load and configure data
                  • 1. Integrate data from multiple sources
                    • 2. Define table structures and properties
                      • 3. Configure data refresh settings
                        Manage and secure Power BI15-20%- 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. Share reports, dashboards, and apps
                                • 2. Embed content in applications or websites
                                  • 3. Monitor usage and performance
                                    - 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%- Perform data analysis
                                          • 1. Create and manage bookmarks and tooltips
                                            • 2. Interpret results and identify trends
                                              • 3. Implement custom visuals and R/Python scripts
                                                - Create reports and dashboards
                                                • 1. Choose appropriate visualizations
                                                  • 2. Apply filters, slicers, and drill-through
                                                    • 3. Design report layout, formatting, and interactivity
                                                      • 4. Create dashboards and pinned elements
                                                        - Enhance reports with analytics
                                                        • 1. Apply conditional formatting and custom visuals
                                                          • 2. Create paginated reports
                                                            • 3. Use AI visuals, forecasts, and key influencers
                                                              Model the data25-30%- Optimize model performance
                                                              • 1. Optimize relationships and calculations
                                                                • 2. Reduce cardinality and data size
                                                                  • 3. Use aggregations and composite models
                                                                    - 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
                                                                            - Create model calculations
                                                                            • 1. Implement aggregation and time intelligence
                                                                              • 2. Use DAX: calculated columns, calculated tables, measures
                                                                                • 3. Use CALCULATE and filter context

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