Exploring the performance measures of big data analytics systems

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.