Exam Objectives:
The Huawei H13-711 HCIA-Big Data V2.0 exam is designed to test a candidate's knowledge of big data concepts and technologies. The exam covers topics such as big data storage, processing, analysis, and application. The main objectives of the exam are:
- Understanding of big data concepts and terminology
- Familiarity with big data storage technologies and architectures
- Knowledge of big data processing technologies and algorithms
- Understanding of big data analysis techniques and tools
- Ability to apply big data technologies to solve business problems
The exam is intended for individuals who want to demonstrate their proficiency in big data technologies and earn the Huawei HCIA-Big Data certification. The exam is suitable for data engineers, data analysts, and other IT professionals who are interested in working with big data.
Exam Details:
The Huawei H13-711 HCIA-Big Data V2.0 exam is a computer-based test that is delivered through Pearson VUE. The exam costs $150 USD and the passing score is 600 out of 1000 points. The exam duration is 90 minutes and it consists of 60 multiple-choice questions. The exam is available in English and Chinese languages.
Related Books:
There are several books that can help candidates prepare for the Huawei H13-711 HCIA-Big Data V2.0 exam. Some of the recommended books include:
- Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset by Pete Warden
- Apache Hadoop YARN: Moving Beyond MapReduce and Batch Processing with Apache Hadoop 2 by Arun C. Murthy and Vinod Kumar Vavilapalli
- Big Data Analytics: A Practical Guide for Managers by Kim H. Pries and Robert Dunnigan
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett
- Hadoop: The Definitive Guide by Tom White
These books cover a wide range of topics related to big data and can help candidates deepen their understanding of the concepts and technologies covered in the exam. They provide practical guidance and real-world examples that can be useful in preparing for the exam and applying big data technologies in the workplace.