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

"Microsoft Power BI Data Analyst (PL-300日本語版)", also known as PL-300 exam, is a Microsoft Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 472 Q&As to your PL-300 Exam preparation. In the PL-300 exam resources, you will cover every field and category in Microsoft Certified: Power BI Data Analyst Associate Certification helping to ready you for your successful Microsoft Certification.

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  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Certification Provider: Microsoft
  • Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate
  • Updated: Sep 11, 2026
  • No. of Questions: 472 Questions & Answers with Testing Engine
  • Download Limit: Unlimited
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What is the exam cost of the Microsoft Power BI Data Analyst Certification Exam

The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

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

Is Microsoft Power BI Data Analyst Certification Exam Worth It

There are many IT certifications available in the market today, but if you are looking for a job as a data analyst then you should give this certification a chance. This certification will help you to stand out from the crowd and get hired easily by many companies. Microsoft Power BI Data Analyst Certification Exam is the most valuable certification program for IT professionals in their respective fields. Microsoft PL-300 Dumps is a must-have certificate for all IT professionals who want to pursue their career in the field of data analytics.

The Microsoft Power BI Data Analyst Certification Exam is a certification exam that will help you to demonstrate your expertise in using the Microsoft Power BI platform. This exam tests the candidate's ability to analyze data with Power BI and create reports that are accurate, insightful and easy to read. Once you pass this exam, you will receive a certificate that shows your competence in performing these tasks. The certificate is valid for three years, so if you want to keep your skills up-to-date then you should take additional training during this time period.

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Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize and analyze data25-30%- Perform data analysis
  • 1. Interpret results and identify trends
    • 2. Implement custom visuals and R/Python scripts
      • 3. Create and manage bookmarks and tooltips
        - Create reports and dashboards
        • 1. Create dashboards and pinned elements
          • 2. Design report layout, formatting, and interactivity
            • 3. Choose appropriate visualizations
              • 4. Apply filters, slicers, and drill-through
                - Enhance reports with analytics
                • 1. Use AI visuals, forecasts, and key influencers
                  • 2. Create paginated reports
                    • 3. Apply conditional formatting and custom visuals
                      Topic 2: Manage and secure Power BI15-20%- Implement security and governance
                      • 1. Manage permissions and access
                        • 2. Configure row-level security (RLS) and object-level security
                          • 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. Create and configure workspaces
                                    • 2. Publish, update, and organize reports/datasets
                                      • 3. Manage data refresh and scheduled updates
                                        Topic 3: Model the data25-30%- Create model calculations
                                        • 1. Use CALCULATE and filter context
                                          • 2. Use DAX: calculated columns, calculated tables, measures
                                            • 3. Implement aggregation and time intelligence
                                              - Design data models
                                              • 1. Create common date tables
                                                • 2. Create relationships: cardinality, cross-filter direction, security
                                                  • 3. Define tables, columns, and hierarchies
                                                    • 4. Implement role-playing dimensions
                                                      - Optimize model performance
                                                      • 1. Reduce cardinality and data size
                                                        • 2. Optimize relationships and calculations
                                                          • 3. Use aggregations and composite models
                                                            Topic 4: Prepare the data25-30%- Load and configure data
                                                            • 1. Define table structures and properties
                                                              • 2. Integrate data from multiple sources
                                                                • 3. Configure data refresh settings
                                                                  - Profile and clean data
                                                                  • 1. Manage data types, columns, and rows
                                                                    • 2. Resolve inconsistencies, null values, and errors
                                                                      • 3. Transform data using Power Query Editor
                                                                        • 4. Evaluate data statistics and column properties
                                                                          - Get or connect to data
                                                                          • 1. Configure data source settings, credentials, and privacy levels
                                                                            • 2. Choose storage modes: Import, DirectQuery, DirectLake
                                                                              • 3. Identify and connect to data sources or shared semantic models
                                                                                • 4. Create and modify parameters

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