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PL-300日本語 Guide Torrent
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)

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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. GuideTorrent Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.

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

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