Microsoft PL-300日本語 dumps - in .pdf

PL-300日本語 pdf
  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Jul 24, 2026
  • Q & A: 515 Questions and Answers
  • PDF Price: $69.99

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  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Jul 24, 2026
  • Q & A: 515 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft PL-300日本語 dumps - Testing Engine

PL-300日本語 Testing Engine
  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Jul 24, 2026
  • Q & A: 515 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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Skills measured

  • Model the data (30-35%)
  • Prepare the data (15-20%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
  • Deploy and maintain assets (20-25%)
  • Visualize and analyze the data (25-30%)

Learn more about the exam

The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.

What is the salary of the Microsoft Power BI Data Analyst Certified professional

The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:

  • United States; USD 90,000

  • United Kingdom; POUNDS 60,000

  • India; INR 500,000

  • Canada; CAD 70,000

  • Australia; AUD 75,000

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

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