PDF Version DemoAbout Exam DA-100: Analyzing Data with Microsoft Power BI
The Microsoft DA-100 test is for those individuals who have at least some experience in working with Power Bi although it is not a strict requirement but a recommendation. In addition, the applicant should have some experience in the concepts of scaling data models, data visualizations, data cleaning, and data processing. When it comes to the test details, DA-100 exam is available in English, Chinese (Simplified), Korean, Japanese and will require $165 for registration. The registered candidate can use the Pearson VUE platform for scheduling an exam. In the final test, individuals will experience around 40-60 items that will have to be solved in 3 hours.
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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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Microsoft DA-100日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Analyze the data | 10-15% | - Perform advanced analytics
|
| Deploy and maintain deliverables | 10-15% | - Secure and share content
|
| Prepare the data | 20-25% | - Get data from data sources
|
| Model the data | 25-30% | - Design data models
|
| Visualize the data | 25-30% | - Create reports
|
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