Title: Open source platform for big data exploration and analysis

Authors: Fernando Almeida; Pavel Kovalevski; Dovydas Sakalauskas

Addresses: INESC TEC, University of Porto, Rua Dr. Roberto Frias, s/n, 4200-465, Porto, Portugal; Polytechnic Institute of Gaya (ISPGaya), Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal ' Polytechnic Institute of Gaya (ISPGaya), Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal ' Polytechnic Institute of Gaya (ISPGaya), Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal

Abstract: Despite the enormous potential of big data, it is a relatively new issue for many companies, particularly for those of smaller size that looks at this as a challenge, is unattainable and only possible for companies with high financial capacity. However, open source software presents itself as an excellent alternative for these companies, which will allow them to exploit the high volume of data they have at their disposal. In this sense, this study presents a proposal for an architecture based exclusively on open source software that includes the entire value chain of big data, from data collection to data analysis. This architecture was tested considering three emerging scenarios in which big data become very relevant and challenging, namely for mobile analytics, network analytics, and mobile analytics.

Keywords: big data; open source; data mining; web analytics; network analytics; mobile analytics.

DOI: 10.1504/IJBIS.2021.119411

International Journal of Business Information Systems, 2021 Vol.38 No.3, pp.418 - 434

Received: 04 Dec 2018
Accepted: 08 Jun 2019

Published online: 26 Nov 2021 *

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