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2018 | OriginalPaper | Chapter

Big Data: Issues, Challenges, and Techniques in Business Intelligence

Authors : Mudasir Ahmad Wani, Suraiya Jabin

Published in: Big Data Analytics

Publisher: Springer Singapore

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Abstract

During the last decade, the most challenging problem the world envisaged was big data problem. The big data problem means that data is growing at a much faster rate than computational speeds. And it is the result of the fact that storage cost is getting cheaper day by day, so people as well as almost all business or scientific organizations are storing more and more data. Social activities, scientific experiments, biological explorations along with the sensor devices are great big data contributors. Big data is beneficial to the society and business but at the same time, it brings challenges to the scientific communities. The existing traditional tools, machine learning algorithms, and techniques are not capable of handling, managing, and analyzing big data, although various scalable machine learning algorithms, techniques, and tools (e.g., Hadoop and Apache Spark open source platforms) are prevalent. In this paper, we have identified the most pertinent issues and challenges related to big data and point out a comprehensive comparison of various techniques for handling big data problem.

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Metadata
Title
Big Data: Issues, Challenges, and Techniques in Business Intelligence
Authors
Mudasir Ahmad Wani
Suraiya Jabin
Copyright Year
2018
Publisher
Springer Singapore
Book
Big Data Analytics

Print ISBN: 978-981-10-6619-1

Electronic ISBN: 978-981-10-6620-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6620-7_59

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