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

PL-300日本語
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Sep 17, 2026
  • Q & A: 472 Questions and Answers

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About Microsoft PL-300日本語 Exam

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 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 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.

  • You have at least one year of experience using Power BI Desktop.

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

Solutions

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This study guide contains everything you will need to have a deep understanding of this certification and take it with confidence. Our experts have taken great care in creating this study guide by using only high-quality resources available on the internet. Our goal is to help you understand each concept so that when taking the exam, there will be no surprises that throw off your momentum or cause you any stress during your preparation or while taking the exam itself.

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

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