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Exam DA-100: Analyzing Data with Microsoft Power BI

Data Analysts enable businesses to maximize the value of their data assets by using Microsoft Power BI. As a subject matter expert, Data Analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. Data Analysts also collaborate with key stakeholders across verticals to deliver relevant insights based on identified business requirements.

The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Part of the requirements for: Microsoft Certified: Data Analyst Associate

Download exam skills outline

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The professionals with the Microsoft Certified: Data Analyst Associate certification are qualified for a variety of job titles. These include a Junior Data Analyst, an Associate Analyst, an Associate Consultant, a Certified Retail Analyst, a Technology Support Analyst, a Digital Media Analyst, and a Network Analyst. The average salary for these positions is $52,000 per annum.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

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Microsoft DA-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Prepare the data20-25%- Clean and transform data
  • 1. Handle missing, duplicate, and inconsistent data
    • 2. Use Power Query Editor for data shaping
      - Get data from data sources
      • 1. Select appropriate storage modes (Import, DirectQuery, Composite)
        • 2. Connect to data sources (files, databases, cloud services)
          Visualize the data25-30%- Create reports
          • 1. Use visuals such as charts, maps, and tables
            • 2. Design interactive reports in Power BI Desktop
              - Enhance reports
              • 1. Use bookmarks and navigation elements
                • 2. Apply filters, slicers, and drill-through
                  Analyze the data10-15%- Analyze data patterns
                  • 1. Identify trends and outliers
                    • 2. Use AI visuals and quick insights
                      - Perform advanced analytics
                      • 1. Apply statistical measures in reports
                        • 2. Use DAX time intelligence functions
                          Deploy and maintain deliverables10-15%- Secure and share content
                          • 1. Share dashboards with users and groups
                            • 2. Implement row-level security (RLS)
                              - Manage workspaces and datasets
                              • 1. Publish reports to Power BI Service
                                • 2. Configure dataset refresh schedules
                                  Model the data25-30%- Design data models
                                  • 1. Design star and snowflake schemas
                                    • 2. Create relationships between tables
                                      - Create calculated columns and measures
                                      • 1. Optimize model performance
                                        • 2. Use DAX for calculations

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