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

  • Exam Code: PL-300日本語
  • Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
  • Updated: Oct 02, 2026
  • Q & A: 472 Questions and Answers

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Microsoft Power BI Data Analyst Exam Certification Details:

Exam Price$165 (USD)
Exam CodePL-300
Passing Score700 / 1000
Schedule ExamPearson VUE
Duration180 mins
Books / TrainingCourse PL-300T00: Microsoft Power BI Data Analyst
Sample QuestionsMicrosoft Power BI Data Analyst Sample Questions
Exam NameMicrosoft Certified - Power BI Data Analyst Associate
Number of Questions40-60

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

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.

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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. Free4Torrent Microsoft PL-300 Dumps are the only way to pass your exam and get certified in your first attempt.

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Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Use DAX: calculated columns, calculated tables, measures
            • 3. Implement aggregation and time intelligence
              - Design data models
              • 1. Create relationships: cardinality, cross-filter direction, security
                • 2. Implement role-playing dimensions
                  • 3. Define tables, columns, and hierarchies
                    • 4. Create common date tables
                      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
                            - Create reports and dashboards
                            • 1. Choose appropriate visualizations
                              • 2. Create dashboards and pinned elements
                                • 3. Apply filters, slicers, and drill-through
                                  • 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
                                          Topic 3: Prepare the data25-30%- Profile and clean data
                                          • 1. Transform data using Power Query Editor
                                            • 2. Manage data types, columns, and rows
                                              • 3. Evaluate data statistics and column properties
                                                • 4. Resolve inconsistencies, null values, and errors
                                                  - 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. Configure data source settings, credentials, and privacy levels
                                                            • 3. Identify and connect to data sources or shared semantic models
                                                              • 4. Create and modify parameters
                                                                Topic 4: Manage and secure Power BI15-20%- Deploy and distribute content
                                                                • 1. Share reports, dashboards, and apps
                                                                  • 2. Embed content in applications or websites
                                                                    • 3. Monitor usage and performance
                                                                      - 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
                                                                            - Manage workspaces and assets
                                                                            • 1. Create and configure workspaces
                                                                              • 2. Publish, update, and organize reports/datasets
                                                                                • 3. Manage data refresh and scheduled updates

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