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Big-data analytics and cloud computing[electronic resource] :theory, algorithms and applications /

Record Type:	Language materials, printed : Monograph/item
[NT 15000414]:	004.6782
Title/Author:	Big-data analytics and cloud computing : theory, algorithms and applications // edited by Marcello Trovati ... [et al.].
other author:	Trovati, Marcello.
Published:	Cham : : Springer International Publishing :, 2015.
Description:	xvi, 169 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
Subject:	Cloud computing.
Subject:	Big data.
Subject:	Computer Science.
Subject:	Probability and Statistics in Computer Science.
Subject:	Computer Communication Networks.
Subject:	Simulation and Modeling.
Subject:	Math Applications in Computer Science.
ISBN:	9783319253138
ISBN:	9783319253114
[NT 15000229]:	This important and timely text/reference 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 This authoritative volume will be of great interest to researchers, enterprise architects, business analysts, IT infrastructure managers and application developers, who will benefit from the valuable insights offered into the adoption of architectures for big data and cloud computing. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface. The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Marcello Trovati serves as a Senior Lecturer in Mathematics, Dr. Richard Hillas a Professor and Head of the Computing and Mathematics Department, Dr. Ashiq Anjum as a Professor of Distributed Computing, Dr. Shao Ying Zhu as a Senior Lecturer in Computing, and Dr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titles Guide to Security Assurance for Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.
Online resource:	http://dx.doi.org/10.1007/978-3-319-25313-8

Big-data analytics and cloud computing[electronic resource] :theory, algorithms and applications /
Big-data analytics and cloud computingtheory, algorithms and applications /[electronic resource] :edited by Marcello Trovati ... [et al.]. - Cham :Springer International Publishing :2015. - xvi, 169 p. :ill., digital ;24 cm.

This important and timely text/reference 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 This authoritative volume will be of great interest to researchers, enterprise architects, business analysts, IT infrastructure managers and application developers, who will benefit from the valuable insights offered into the adoption of architectures for big data and cloud computing. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface. The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Marcello Trovati serves as a Senior Lecturer in Mathematics, Dr. Richard Hillas a Professor and Head of the Computing and Mathematics Department, Dr. Ashiq Anjum as a Professor of Distributed Computing, Dr. Shao Ying Zhu as a Senior Lecturer in Computing, and Dr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titles Guide to Security Assurance for Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.

ISBN: 9783319253138

Standard No.: 10.1007/978-3-319-25313-8doiSubjects--Topical Terms:

367267
Cloud computing.

LC Class. No.: QA76.585

Dewey Class. No.: 004.6782

Big-data analytics and cloud computing[electronic resource] :theory, algorithms and applications /
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