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

• Main Authors: Jusoh, Yusmadi Yah, Abdullah, Rusli, Nor, Rozi Nor Haizan, Yahaya, Jamaiah, Muhammad, Shireen, Arunachalam, Aishwharya Raani
• Format: Conference or Workshop Item
• Published: IEEE 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/37572/; https://ieeexplore.ieee.org/document/10145076

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.