Scalable Computing and Communications

Distributed Computing in Big Data Analytics

Concepts, Technologies and Applications

Editors: Mazumder, Sourav, Singh Bhadoria, Robin, Deka, Ganesh Chandra (Eds.)

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  • Addresses key concepts and patterns of distributed computing to provide practitioners with insight while designing big data analytics use cases
  • Details how different big data technologies leverage those key concepts and patterns of distributed computing
  • Includes applications, such as IoT, cognitive analytics, social media analytics and scientific data analytics
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eBook 91,62 €
price for Spain (gross)
  • ISBN 978-3-319-59834-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 114,39 €
price for Spain (gross)
  • ISBN 978-3-319-59833-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 114,39 €
price for Spain (gross)
  • ISBN 978-3-319-86713-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.

This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations.

Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

Table of contents (9 chapters)

Table of contents (9 chapters)

Buy this book

eBook 91,62 €
price for Spain (gross)
  • ISBN 978-3-319-59834-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 114,39 €
price for Spain (gross)
  • ISBN 978-3-319-59833-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 114,39 €
price for Spain (gross)
  • ISBN 978-3-319-86713-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Distributed Computing in Big Data Analytics
Book Subtitle
Concepts, Technologies and Applications
Editors
  • Sourav Mazumder
  • Robin Singh Bhadoria
  • Ganesh Chandra Deka
Series Title
Scalable Computing and Communications
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-59834-5
DOI
10.1007/978-3-319-59834-5
Hardcover ISBN
978-3-319-59833-8
Softcover ISBN
978-3-319-86713-7
Series ISSN
2520-8632
Edition Number
1
Number of Pages
X, 162
Number of Illustrations
9 b/w illustrations, 63 illustrations in colour
Topics