Big Data Analytics Methods and Applications
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analyt
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Data Analytics Methods and Applications
Big Data Analytics
Saumyadipta Pyne ⋅ B.L.S. Prakasa Rao S.B. Rao Editors
Big Data Analytics Methods and Applications
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Editors Saumyadipta Pyne Indian Institute of Public Health Hyderabad India
S.B. Rao CRRao AIMSCS University of Hyderabad Campus Hyderabad India
B.L.S. Prakasa Rao CRRao AIMSCS University of Hyderabad Campus Hyderabad India
ISBN 978-81-322-3626-9 DOI 10.1007/978-81-322-3628-3
ISBN 978-81-322-3628-3
(eBook)
Library of Congress Control Number: 2016946007 © Springer India 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer (India) Pvt. Ltd. The registered company address is: 7th Floor, Vijaya Building, 17 Barakhamba Road, New Delhi 110 001, India
Foreword
Big data is transforming the traditional ways of handling data to make sense of the world from which it is collected. Statisticians, for instance, are used to developing methods for analysis of data collected for a specific purpose in a planned way. Sample surveys and design of experiments are typical examples. Big data, in contrast, refers to massive amounts of very high dimensional and even unstructured data which are continuously produced and stored with much cheaper cost than they are used to be. High dimensionality combined with large sample size creates unprecedented issues such as heavy computational cost and algorithmic instability. The massive samples in big data are typically aggregated from multiple sources at different time points using different technologies. This can create issues of heterogeneity, experimental variations, and statistical biases, and would therefore require the researchers and practitioners to develop more adaptive and robust procedures. Toward this, I am extremely happy to see in this title not just a compilation of chapters written by international experts who work in diverse disciplines involving Big Data, but
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