Big Data and Visual Analytics 2017 Edition, ISBN-13: 978-3319639154


Big Data and Visual Analytics 2017 Edition, ISBN-13: 978-3319639154

[PDF eBook eTextbook]


  • 273 pages
  • Publisher: Springer; 1st ed. 2017 edition (January 17, 2018)
  • Author(s): Sang C. Suh, Thomas Anthony
  • Language: English
  • ISBN-10: 3319639153
  • ISBN-13: 978-3319639154


This book provides users with cutting edge methods and technologies in the area of  big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics.

Each chapter covers  specific topics related to big data and data analytics as virtual data machine, security of  big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics.

This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.

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