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

PL-300日本語 actual test
  • Exam Code: PL-300J
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Jul 29, 2026
  • Q & A: 515 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $69.99  

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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.

Why Microsoft Power BI Data Analyst Certification Exam is so difficult

No matter how many times you take the Microsoft Power BI Data Analyst Certification Exam, you will never be able to finish it. This is because the exam is designed to be as difficult as possible. When you first sit down and begin answering questions, you may feel like there are a lot of easy ones. This is just part of the test's strategy. they want to make sure that you think everything's going smoothly, so that when they throw in a difficult question later on, it will be much harder for you to answer.

The Microsoft certification exams are considered to be the toughest in the industry. This is because of the fact that if you have passed one of these exams, then it means that you have gone through a tough time and have shown that you are capable enough to handle any situation. Microsoft Power BI Data Analyst Certification Exam is designed to give you a hard time. It won't let up until you finally give up entirely and surrender your certification. Actual4test Microsoft PL-300 Dumps are the only way to pass your exam and get certified in your first attempt.

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

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:

  • Canada; CAD 70,000

  • Australia; AUD 75,000

  • United Kingdom; POUNDS 60,000

  • India; INR 500,000

  • United States; USD 90,000

The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT

The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.

There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at Actual4test our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.

Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- Deploy and distribute content
  • 1. Monitor usage and performance
    • 2. Share reports, dashboards, and apps
      • 3. Embed content in applications or websites
        - Manage workspaces and assets
        • 1. Publish, update, and organize reports/datasets
          • 2. Manage data refresh and scheduled updates
            • 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
                    Topic 2: 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
                          - Enhance reports with analytics
                          • 1. Create paginated reports
                            • 2. Use AI visuals, forecasts, and key influencers
                              • 3. Apply conditional formatting and custom visuals
                                - Create reports and dashboards
                                • 1. Choose appropriate visualizations
                                  • 2. Create dashboards and pinned elements
                                    • 3. Design report layout, formatting, and interactivity
                                      • 4. Apply filters, slicers, and drill-through
                                        Topic 3: 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. 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
                                                      - Profile and clean data
                                                      • 1. Manage data types, columns, and rows
                                                        • 2. Transform data using Power Query Editor
                                                          • 3. Evaluate data statistics and column properties
                                                            • 4. Resolve inconsistencies, null values, and errors
                                                              Topic 4: Model the data25-30%- Optimize model performance
                                                              • 1. Optimize relationships and calculations
                                                                • 2. Use aggregations and composite models
                                                                  • 3. Reduce cardinality and data size
                                                                    - 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
                                                                            - Create model calculations
                                                                            • 1. Implement aggregation and time intelligence
                                                                              • 2. Use CALCULATE and filter context
                                                                                • 3. Use DAX: calculated columns, calculated tables, measures

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