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DA-100 pdf
  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Sep 03, 2026
  • Q & A: 150 Questions and Answers
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  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Sep 03, 2026
  • Q & A: 150 Questions and Answers
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DA-100 Testing Engine
  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Sep 03, 2026
  • Q & A: 150 Questions and Answers
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Microsoft DA-100 Practice Test Questions, Microsoft DA-100 Exam Practice Test Questions

The candidates who want to earn the Microsoft Certified: Data Analyst Associate certification must pass one qualifying exam, which is Microsoft DA-100. This test evaluates the ability of the test takers to accomplish specific technical tasks. These include the processes with data, such as analyzing, preparing, maintaining and deploying, visualizing, and modeling.

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

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4. Data Analysis (10-15%):

This section requires your skills in:

  • Enhancing reports to expose insights: The candidates should have the expertise in personalizing visuals, applying filters & slicers and conditional formatting. They also need to demonstrate their skills in exploring statistical summary, creating reference lines with Analytics pane, and using Q&A visuals, among others.
  • Caring out advanced analysis: This subject area covers your skills in identifying outliers, using binnings & groupings, conducting Time Series Analysis, and applying AI Insights. The students should also have competence in using decomposition tree visuals to dissect a measure and use Key Influencers for the exploration of dimensional variances.

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Microsoft DA-100 Exam Syllabus Topics:

SectionWeightObjectives
Deploy and maintain deliverables10-15%- Manage workspaces and datasets
- Share and distribute content
- Configure refresh and security
Model the data25-30%- Create calculated tables and columns
- Optimize model performance
- Create measures using DAX
- Design and develop data models
Visualize the data20-25%- Create reports and dashboards
- Enrich reports for usability
- Apply filters, slicers, and formatting
Analyze the data10-15%- Apply AI visuals and insights
- Perform advanced analysis
- Identify patterns and trends
Prepare the data20-25%- Clean, transform, and load data
- Profile and examine data
- Get data from different sources

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