Название: Data Intensive Computing Applications for Big Data Автор: M. Mittal, V.E. Balas, D.J. Hemanth, R. Kumar
Издательство: IOS Press
ISBN: 1614998132
Год: 2018
Страниц: 620
Язык: английский
Формат: True PDF
Размер: 45.0 MB
The book Data Intensive Computing Applications for Big Data discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications.
It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment.
The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.
Key Features:
Overview of big data analysis using parallel computing.
Addresses the complete data science workflow in the cloud.
Explores basic and high level concepts, thus serving as a manual for those in the industry while also helping beginners to understand both basic and advanced aspects.
Examines privacy issues and challenges in a data-intensive cloud computing environment.
Based on the latest technologies, and covering the major changes and advances in big data analysis.
Explains concepts of parallel and distributed computing technologies and their applications in the real world.
Data processing and security solutions in the cloud.
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