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“Problem Solving with C++ 10th Edition by Walter Savitch, ISBN-13: 978-0134448282” has been added to your cart. View cart
Big Data and Visual Analytics 2017 Edition, ISBN-13: 978-3319639154
Home Computing Big Data and Visual Analytics 2017 Edition, ISBN-13: 978-3319639154
Big Data Fundamentals: Concepts, Drivers & Techniques by Thomas Erl, ISBN-13: 978-0134291079
Big Data Fundamentals: Concepts, Drivers & Techniques by Thomas Erl, ISBN-13: 978-0134291079 $50.00 Original price was: $50.00.$9.99Current price is: $9.99.
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Big Data Analysis with Python: Combine Spark and Python by Ivan Marin, ISBN-13: 978-1789955286
Big Data Analysis with Python: Combine Spark and Python by Ivan Marin, ISBN-13: 978-1789955286 $50.00 Original price was: $50.00.$14.99Current price is: $14.99.

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

$50.00 Original price was: $50.00.$14.99Current price is: $14.99.

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Category: Computing Tags: Big Data and Visual Analytics 2017 Edition, ISBN-13: 978-3319639154, Sang C. Suh, Thomas Anthony
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Description

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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