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Skills measured

  • Deploy and maintain deliverables (10-15%)
  • Visualize the data (20-25%)
  • Prepare the data (20-25%)
  • Model the data (25-30%)
  • Analyze the data (10-15%)

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Target Audience

The potential candidates for the Microsoft DA-100 exam are Data Analysts. These professionals have the responsibility of enabling organizations to optimize their data asset values through the use of Microsoft Power BI. They also have the job responsibility of building and designing scalable data models, facilitating advanced analytics capacities, and transforming and cleaning data. These duties are aimed to offer significant business values through easy-to-understand data visualization. The Data Analysts also partner with the major stakeholders to deliver significant insights according to the identified business prerequisites.

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

What should you know about the Microsoft DA-100 exam before going for it?

The intended candidates for the Microsoft DA-100 exam are Data Analysts. These professionals help the organizations make the most of the value of data assets through the use of Microsoft Power BI. They also collaborate with the major stakeholders across the company to deliver the appropriate insights based on the recognized business prerequisites.

Microsoft DA-100 is an associate-level certification test, and as such, it does not have any official prerequisites. However, Microsoft recommends that the students have a good fundamental knowledge of data processing and data repositories both in Cloud and on-premises. The candidates for the exam should have the relevant skills in building and designing scalable data models, facilitating advanced analytic abilities, and transforming and cleaning data to provide significant business value through understandable data visualizations.

Microsoft DA-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Analyze the data10-15%- Perform advanced analytics
  • 1. Use DAX time intelligence functions
    • 2. Apply statistical measures in reports
      - Analyze data patterns
      • 1. Identify trends and outliers
        • 2. Use AI visuals and quick insights
          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%- Create calculated columns and measures
                  • 1. Optimize model performance
                    • 2. Use DAX for calculations
                      - Design data models
                      • 1. Design star and snowflake schemas
                        • 2. Create relationships between tables
                          Prepare the data20-25%- Get data from data sources
                          • 1. Connect to data sources (files, databases, cloud services)
                            • 2. Select appropriate storage modes (Import, DirectQuery, Composite)
                              - Clean and transform data
                              • 1. Use Power Query Editor for data shaping
                                • 2. Handle missing, duplicate, and inconsistent data
                                  Visualize the data25-30%- Enhance reports
                                  • 1. Use bookmarks and navigation elements
                                    • 2. Apply filters, slicers, and drill-through
                                      - Create reports
                                      • 1. Use visuals such as charts, maps, and tables
                                        • 2. Design interactive reports in Power BI Desktop

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