Big-Data Analytics and Cloud Computing: Theory, Algorithms and Applications

Trovati, Marcello; Hill, Richard; Anjum, Ashiq; Zhu, Shao Ying; Liu, Lu

This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Details

Published by: Springer

Publication Date: 2018-03-30

Format: Paperback

ISBN-13: 9783319797670

DOI: 10.1007/978-3-319-25313-8

Dimensions: 235cm x155cm

Pages: 169