Big Data Computing (Hardback) book cover

Big Data Computing

Edited by Rajendra Akerkar

© 2013 – Chapman and Hall/CRC

564 pages | 114 B/W Illus.

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Hardback: 9781466578371
pub: 2013-12-05
eBook (VitalSource) : 9781466578388
pub: 2013-12-05
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Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. 

Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches.  

Comprised of five sections, the book focuses on:

  • What Big Data is and why it is important
  • Semantic technologies
  • Tools and methods
  • Business and economic perspectives
  • Big Data applications across industries

Table of Contents

Section I Introduction

Toward Evolving Knowledge Ecosystems for Big Data Understanding

Vadim Ermolayev, Rajendra Akerkar, Vagan Terziyan, and Michael Cochez

Tassonomy and Review of Big Data Solutions Navigation

Pierfrancesco Bellini, Mariano di Claudio, Paolo Nesi, and Nadia Rauch

Big Data: Challenges and Opportunities

Roberto V. Zicari

Section II Semantic Technologies and Big Data

Management of Big Semantic Data

Javier D. Fernández, Mario Arias, Miguel A. Martínez-Prieto, and Claudio Gutiérrez

Linked Data in Enterprise Integration

Sören Auer, Axel-Cyrille Ngonga Ngomo, Philipp Frischmuth, and Jakub Klimek

Scalable End-User Access to Big Data

Martin Giese, Diego Calvanese, Peter Haase, Ian Horrocks, Yannis Ioannidis, Herald Kllapi, Manolis Koubarakis, Maurizio Lenzerini, Ralf Möller, Özgür Özçep, Mariano Rodriguez Muro, Riccardo Rosati, Rudolf Schlatte, Michael Schmidt, Ahmet Soylu, and Arild Waaler

Semantic Data Interoperability: The Key Problem of Big Data

Hele-Mai Haav and Peep Küngas

Section III Big Data Processing

Big Data Exploration

Stratos Idreos

Big Data Processing with MapReduce

Jordà Polo

Efficient Processing of Stream Data over Persistent Data

M. Asif Naeem, Gillian Dobbie, and Gerald Weber

Section IV Big Data and Business

The Economics of Big Data: A Value Perspective on State of the Art and Future Trends

Tassilo Pellegrin

Advanced Data Analytics for Business

Rajendra Akerkar

Section V Big Data Applications

Big Social Data Analysis

Erik Cambria, Dheeraj Rajagopal, Daniel Olsher, and Dipankar Das

Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings

Dario Bonino, Fulvio Corno, and Luigi De Russis

Big Data Application: Analyzing Real-Time Electric Meter Data

Mikhail Simonov, Giuseppe Caragnano, Lorenzo Mossucca, Pietro Ruiu, and Olivier Terzo

Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information

Bin Jiang and Xintao Liu

Big Textual Data Analytics and Knowledge Management

Marcus Spies and Monika Jungemann-Dorner

Subject Categories

BISAC Subject Codes/Headings:
BUSINESS & ECONOMICS / Information Management
COMPUTERS / Database Management / General
COMPUTERS / Database Management / Data Mining