Pass your actual test with our Microsoft DA-100 training material at first attempt
Last Updated: Aug 11, 2026
No. of Questions: 150 Questions & Answers with Testing Engine
Download Limit: Unlimited
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Microsoft DA-100, also known as Analyzing Data with Microsoft Power BI, is a certification exam that validates an individual's ability to use Power BI to analyze and visualize data. DA-100 exam is designed for data professionals who are looking to enhance their skills and demonstrate their expertise in the field of data analysis. It is an excellent certification for those who want to advance their careers in the data industry.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
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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
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| Section | Weight | Objectives |
|---|---|---|
| Deploy and maintain deliverables | 10-15% | - Configure refresh and security - Manage workspaces and datasets - Share and distribute content |
| Prepare the data | 20-25% | - Profile and examine data - Get data from different sources - Clean, transform, and load data |
| Model the data | 25-30% | - Create calculated tables and columns - Optimize model performance - Create measures using DAX - Design and develop data models |
| Visualize the data | 20-25% | - Apply filters, slicers, and formatting - Create reports and dashboards - Enrich reports for usability |
| Analyze the data | 10-15% | - Apply AI visuals and insights - Identify patterns and trends - Perform advanced analysis |
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