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Last Updated: Nov 08, 2026
No. of Questions: 150 Questions & Answers with Testing Engine
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The candidates can explore various resources to prepare for the Microsoft DA-100 exam. The Microsoft Learning Platform offers many study tools that the learners can use to achieve success in their test. The first step in the preparation process is to go over the detailed exam topics. After that, you can choose your resources carefully. Here are the official recommended materials for the DA-100 test:
Microsoft recommends the Analyzing Data with Power BI training course for the candidates taking the DA-100 test. This training focuses on different best practices and methods associated with the technical and business requirements for visualizing, analyzing, and modeling data with Power BI. The individuals will learn how to process and access data from different data sources, including non-relational and relational data.
The recommended book resource for this test is Exam Ref: DA-100 Analyzing Data with Microsoft Power BI by Daniil Maslyuk. This is a professional-level resource to help the learners optimize their performance in the test and improve their skills. The book can be found on the Microsoft Press Store.
The applicants who prefer self-paced study can explore the learning paths for the Microsoft DA-100 exam. There are six learning paths for this certification test, including Getting Started with Microsoft Data Analytics, Prepare Data for Analysis, Model Data in Power BI, and Visualize Data in Power BI, among others. Each path contains different modules that address particular topics of the exam.
Microsoft also offers the official practice test for Microsoft DA-100. The exam questions cover all the objectives of the actual test. This means that you will be well prepared for any questions that may be administered in the exam.
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The following will be discussed in MICROSOFT DA-100 exam dumps:
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare the data | 20-25% | - Clean and transform data
|
| Topic 2: Deploy and maintain deliverables | 10-15% | - Secure and share content
|
| Topic 3: Model the data | 25-30% | - Create calculated columns and measures
|
| Topic 4: Visualize the data | 25-30% | - Enhance reports
|
| Topic 5: Analyze the data | 10-15% | - Analyze data patterns
|
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