Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data

Burhanullah  Khattak; Aurangzeb  Khan; Khairullah  Khan; Wahab Khan; Muhammad Kamran; Muhammad Fahad

Research Article

Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data

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@ARTICLE{10.4108/eai.13-7-2018.159621,
    author={Burhanullah  Khattak and Aurangzeb  Khan and Khairullah  Khan and Wahab Khan and Muhammad Kamran and Muhammad Fahad},
    title={Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data},
    journal={EAI Endorsed Transactions on Scalable Information Systems},
    volume={6},
    number={23},
    publisher={EAI},
    journal_a={SIS},
    year={2019},
    month={7},
    keywords={Hadoop, velocity, big data, variety, volume},
    doi={10.4108/eai.13-7-2018.159621}
}

Burhanullah Khattak
Aurangzeb Khan
Khairullah Khan
Wahab Khan
Muhammad Kamran
Muhammad Fahad
Year: 2019
Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data
SIS
EAI
DOI: 10.4108/eai.13-7-2018.159621

Burhanullah Khattak¹, Aurangzeb Khan¹, Khairullah Khan¹, Wahab Khan²^,*, Muhammad Kamran³, Muhammad Fahad¹

1: Department of Computer Science, University of Science & Technology Bannu, Pakistan
2: Department of Computer Science & Software Engineering, IIU, Islamabad 44000, Pakistan
3: Department of Electronics, University of Peshawar, Pakistan

*Contact email: Wahab.phdcs72@iiu.edu.pk

Abstract

Here in this study, we provide an empirical analysis of recent advances, characteristic and challenges of big data. Initially, we acquaint the readers with the general background, history, and characteristics of big data including volume, velocity, value and variety etc. The scope of applications for big data including political services and government monitoring, enterprise management, scientific research, public utilities, public administration and internet of things are illustrated. A detailed analysis is presented regarding opportunities and challenges faced by the public and private sectors during analysis phase of big data management such as storing, visualizing, capturing and so on. In addition, we investigated and reported a detailed empirical analysis of the most recent management tools like Hadoop and MapReduce, along with their different components, usage, and limitation. Finally, open issues and future directions for this new and dynamic area of research are provided. The primary objective of this empirical analysis is to present a broad-spectrum perspective of this emerging research area with the goal to present big data related concepts in a coherent manner to the beginners.

Keywords: Hadoop, velocity, big data, variety, volume

Received: 2018-11-07
Accepted: 2019-07-15
Published: 2019-07-24
Publisher: EAI

: http://dx.doi.org/10.4108/eai.13-7-2018.159621

Copyright © 2019 Burhanullah Khattak et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.