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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

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The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Identifying sources of data that can contribute to achieving business goals

  • Creating custom data models that support analysis and reporting requirements

  • Developing dashboards that provide actionable insights into business performance

  • Understanding business context, including organizational strategy and objectives

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Skills measured

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

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.

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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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