International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 10, Issue 1 (January 2023), Pages: 92-104

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 Review Paper

 Exploring the performance measures of big data analytics systems

 Author(s): Ismail Mohamed Ali 1, Yusmadi Yah Jusoh 2, *, Rusli Abdullah 2, Yahye Abukar Ahmed 1

 Affiliation(s):

 1Faculty of Computing, SIMAD University, Mogadishu, Somalia
 2Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-7767-5001

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2023.01.013

 Abstract:

Performance measurement is the process of making an evidence-based improvement. It reveals the performance gains or gaps, depending on the entity to be measured, being an organization, people, equipment, processes, or systems. After development, big data analytics (BDA) systems massively fail in organizational settings. The reasons, however, are not fully understood. This paper investigates how organizations can quantify the performance of their BDA systems. To answer this question, we investigated performance measures and performance-contributing factors in the existing literature and surveyed users’ perceptions of our findings. The results show that metrics of efficiency and effectiveness can be used to measure the performance of the BDA system. The results also demonstrate that technology, competency, and working conditions are the key factors that contribute to the performance of the BDA system.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Big data, Big data analytics, BDA process, Performance measures, Performance-contributing factors

 Article History: Received 9 May 2022, Received in revised form 21 August 2022, Accepted 27 September 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Ali IM, Jusoh YY, Abdullah R, and Ahmed YA (2023). Exploring the performance measures of big data analytics systems. International Journal of Advanced and Applied Sciences, 10(1): 92-104

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 

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