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Towards eco-sustainability and green analytics model to measure the performance of big data systems


Citation

Jusoh, Yusmadi Yah and Abdullah, Rusli and Nor, Rozi Nor Haizan and Yahaya, Jamaiah and Muhammad, Shireen and Arunachalam, Aishwharya Raani (2023) Towards eco-sustainability and green analytics model to measure the performance of big data systems. In: 2023 9th International Conference on Information Management (ICIM 2023), 17-19 Mar. 2023, Oxford, United Kingdom. (pp. 1-6).

Abstract

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needs to understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of their BDS.


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Official URL or Download Paper: https://ieeexplore.ieee.org/document/10145076

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1109/ICIM58774.2023.00007
Publisher: IEEE
Keywords: Big data systems (BDS); Performances measures; Eco-sustainability; Green analytics metrics
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 28 Sep 2023 03:50
Last Modified: 28 Sep 2023 03:50
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICIM58774.2023.00007
URI: http://psasir.upm.edu.my/id/eprint/37572
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