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Big-data Analytics and Cloud Computing: Theory, Algorithms and Applications
By Lu Liu (editor), Shao Ying Zhu (editor), Marcello Trovati (editor), Richard Hill (editor) and Ashiq Anjum (editor)
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Bibliographic Detail
Publisher Springer-Verlag New York Inc
Publication date January 19, 2016
Binding Hardcover
Book category Adult Non-Fiction
ISBN-13 9783319253114
ISBN-10 3319253115
Dimensions 0.75 by 9.50 by 9.50 in.
Weight 0.90 lbs.
Published in Europe
Original list price $89.99
Summaries and Reviews
Amazon.com description: Product Description:

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.



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Hardcover
Book cover for 9783319253114
 
The price comparison is for this edition
With Ashiq Anjum (other contributor), Richard Hill (other contributor), Shao Ying Zhu (other contributor), Marcello Trovati (other contributor) | from Springer-Verlag New York Inc (January 19, 2016)
9783319253114 | details & prices | 9.50 × 9.50 × 0.75 in. | 0.90 lbs | List price $89.99
About: 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.

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