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Review Article · Open access · Published 22 June 2020

Big Data Characteristics, Architecture, Technologies and Applications

Wisam A. Qader1, Musa M. Ameen1 & Bilal Ismael Ahmed1

Journal of Computer Science, Volume 16, Issue 6, pp. 817–824 · doi.org/10.3844/jcssp.2020.817.824

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Abstract

Big Data is a vast volume of data that is not easy to be stored or processed with conventional approaches within a limited period. Therefore, to manage and extract value from it, a new architecture, method and analysis are needed. Big Data poses many challenges and problems and it has different properties such as volume, velocity, variety and veracity. The goal of Big Data is not only to collect, save and organize huge volumes of data, but it is also used to evaluate, extract and visualize useful information for further processes. Big Data is a modern worldwide novel technology that has the potential to provide great benefits to business and organizations of different fields around the world and it will be more desirable in the next few years. This work describes the importance of Big Data, various challenges it faces in adapting to today’s modern era, characteristics and architecture of Big Data, technologies used in Big Data and applications created using Big Data. The paper also explains MapReduce and Hadoop Distributed File System as two important models of Big Data.

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Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

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Qader, W. A., Ameen, M. M. & Ahmed, B. I. (2020). Big Data Characteristics, Architecture, Technologies and Applications. Journal of Computer Science, 16(6), 817–824. https://doi.org/10.3844/jcssp.2020.817.824

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Volume 16, Issue 6
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Big Data Characteristics, Architecture, Technologies and ApplicationsJournal of Computer Science · Volume 16, Issue 6 · pp. 817–824 · CC BY 3.0Download