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More about DA-100 Exam
This test focuses on technical domains such as structuring data, using DAX to create measures, making a data model, acquiring data from numerous sources, and preparing and analyzing data. Also, it checks one’s skills in interpreting reports, revealing data insights, forming dashboards, visualizing data, handling datasets, and lastly, incorporating and maintaining deliverables. The registration fee for DA-100 is $165. The test is available in numerous languages including Japanese, Chinese, Korean, and English. DA-100 can be taken at local physical centers or online under proctored conditions.
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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Analyze the data
The following will be discussed in MICROSOFT DA-100 exam dumps:
- Create reference lines by using Analytics pane
- Apply conditional formatting
- Use groupings and binnings
- Use the decomposition tree visual to break down a measure
- Perform advanced analysis
- Apply slicers and filters
- Conduct Time Series analysis
- Perform top N analysis
- Use the Key Influencers to explore dimensional variances
- Add a Quick Insights result to a report
- Identify outliers
- Personalize visuals
- Use the Q&A visual
- Explore statistical summary
- Apply AI Insights
- Enhance reports to expose insights
- Use the Play Axis feature of a visualization
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Useful Books to Pass DA-100
Those preparing for DA-100 test can incorporate the following books from Amazon in their learning process to ensure they pass the exam with high scores:
- ‘Exam Ref DA-100 Analyzing Data with Microsoft Power BI 1st Edition’ by Daniil Maslyuk. This is the official book issued by Microsoft for its DA-100 test. The guidance offered in this paperback aims to help candidates acquire all the right skills needed for the exam so they will be able to achieve a high score. The book puts great emphasis on real-world issues and problems so the readers will know what to expect when working in the job role of a data analyst. It provides complete coverage of all the tested objectives, and this content is extremely detailed. The material also includes various ‘what if’ scenarios to encourage critical thinking in students and prepare them for the more challenging exam questions.
- ‘Secrets of DA-100 Analyzing Data with Microsoft Power BI’ by Nikhil J. This Kindle e-book is packed with numerous up-to-date questions & answers for the Microsoft DA-100 exam in order to help students score better. By going through this material, the applicants will assess themselves and will understand how well they can apply all the things they learnt in theory. The e-book has a good track record of helping individuals achieve success in DA-100 test.
- ‘Exam DA-100: Data Analyst Associate 25 Test Prep Questions Version II’ by Ger Arevalo. This guide can act as supplementary material when going through hands-on practice, labs, and classes for DA-100. The intent of this book is to reinforce what you learn, and it is also a good last-minute tool that can help students identify their level of readiness. It will help candidates acquire competencies that will be beneficial when working out in the real world.
- ‘Learn How to Pass DA-100: Analyzing Data with Microsoft Power BI Exam’. Prepared by Rodrezil Publications, this book compiles advice and tips from candidates who have already passed DA-100 exam and hence offers invaluable first-hand experiences. It also provides the readers with advice from IT experts who know all the ins and outs of the test and know how to deliver this knowledge in an easy-to-understand manner. The goal of this Kindle e-book is to help applicants get over the fear of the exam and pass it on their very first attempt. The material also comes with coupon codes that students can use to take free DA-100 mock tests at Vullam for better preparation and prior self-assessment.
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Microsoft DA-100日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Deploy and maintain deliverables | 10% | - Manage datasets
|
| Model the data | 30% | - Develop a data model
|
| Prepare the data | 20% | - Get data from different data sources
|
| Visualize the data | 25% | - Create dashboards
|
| Analyze the data | 15% | - Perform advanced analysis
|


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