Big Data

Principles and Paradigms

Nonfiction, Computers, Database Management, Data Processing, General Computing
Cover of the book Big Data by , Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9780128093467
Publisher: Elsevier Science Publication: June 7, 2016
Imprint: Morgan Kaufmann Language: English
Author:
ISBN: 9780128093467
Publisher: Elsevier Science
Publication: June 7, 2016
Imprint: Morgan Kaufmann
Language: English

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.

To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.

  • Covers computational platforms supporting Big Data applications
  • Addresses key principles underlying Big Data computing
  • Examines key developments supporting next generation Big Data platforms
  • Explores the challenges in Big Data computing and ways to overcome them
  • Contains expert contributors from both academia and industry
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.

To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.

More books from Elsevier Science

Cover of the book Particles at Interfaces by
Cover of the book Quantum Inspired Computational Intelligence by
Cover of the book Advances in Botanical Research by
Cover of the book Handbook of Natural Gas Transmission and Processing by
Cover of the book Security Leader Insights for Business Continuity by
Cover of the book The Definitive Guide to the ARM Cortex-M3 by
Cover of the book Working Guide to Pump and Pumping Stations by
Cover of the book Fusion Technology 1996 by
Cover of the book The Sedimentary Basins of the United States and Canada by
Cover of the book Well Testing Project Management by
Cover of the book Dust Explosion Dynamics by
Cover of the book Advances in Computers by
Cover of the book Practical Petrophysics by
Cover of the book Insights into Enzyme Mechanisms and Functions from Experimental and Computational Methods by
Cover of the book Molecular Medical Microbiology by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy