Title: XEW 2.0: big data analytics tool based on swarm intelligence

Authors: Fadwa Bouhafer; Anass El Haddadi; Mohammed Heyouni; Ouafaa Ben Ali

Addresses: DSCI Team, Department of Mathematics and IT, National School of Applied Sciences, BP 03, Ajdir, Al-Hoceima, Morocco ' DSCI Team, Department of Mathematics and IT, National School of Applied Sciences, BP 03, Ajdir, Al-Hoceima, Morocco ' DSCI Team, Department of Mathematics and IT, National School of Applied Sciences, BP 03, Ajdir, Al-Hoceima, Morocco ' DSCI Team, Department of Mathematics and IT, National School of Applied Sciences, BP 03, Ajdir, Al-Hoceima, Morocco

Abstract: Nowadays, data is a golden capital for any business organisation that wants to improve their business. The big organisations and the most reputed ones do not only think to collect data, but they make continuous efforts to use this data for efficient decision-making. Data visualisation plays a crucial importance in big data analysis. The existence of various data visualisation methods can be confusing for users to choose the most appropriate. In this paper, we present the big data analytics tool XEW 2.0 based on swarm intelligence, especially the ant colony optimisation. XEW 2.0 design is based on a detailed study of data visualisation. This study presents a guide for choosing data visualisation methods, and how the traditional methods are improved to meet the big data visualisations need.

Keywords: big data visualisation; big data analytics; incremental clustering; ant colony optimisation; swarm intelligence; XEW 2.0.

DOI: 10.1504/IJMIS.2020.114776

International Journal of Multimedia Intelligence and Security, 2020 Vol.3 No.4, pp.348 - 370

Received: 26 Sep 2019
Accepted: 23 Feb 2020

Published online: 16 Apr 2021 *

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