Big-data analytics and cloud computing: Theory, algorithms and applications

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

Research output: Book/ReportBook

1 Citation (Scopus)

Abstract

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. © Springer International Publishing Switzerland 2016.
Original languageEnglish
PublisherSpringer International Publishing AG
ISBN (Print)9783319253138
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes

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Trovati, M., Hill, R., Anjum, A., Zhu, S. Y., & Liu, L. (2016). Big-data analytics and cloud computing: Theory, algorithms and applications. Springer International Publishing AG. https://doi.org/10.1007/978-3-319-25313-8