Title: Towards a systematic collect data process

Authors: Iman Tikito; Nissrine Souissi

Addresses: Mohammed V University in Rabat, EMI-SIWEB Team, Rabat, Morocco ' Computer Sciences Department, Mines-Rabat School, Rabat Morocco

Abstract: Big data has become a known topic by a large number of researchers in different areas. Actions to improve data lifecycle in big data context were conduct in different phases and focused mainly on problems such as storage, security, analysis and visualisation. In this paper, we focus basically on improvement of collect phase, which make the other phases more efficient and effective. We propose in this paper a process to follow to resolve the problematic of collecting a huge amount of data and as a result, optimise data lifecycle. To do this, we analyse different data collect processes present in literature and identify the similitude with the process of systematic literature review. We apply our process by mapping the seven characteristics of big data with the sub-processes of proposed collect data process. This mapping provides a guide for the customer to have a clear decision of the need to use the proposed process by answering a set of questions.

Keywords: big data; data collect; data lifecycle; systematic literature review; SLR; process.

DOI: 10.1504/IJBDI.2020.107374

International Journal of Big Data Intelligence, 2020 Vol.7 No.2, pp.72 - 84

Received: 07 Nov 2018
Accepted: 13 Aug 2019
Published online: 21 May 2020 *

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