The taxonomical distinction between the concepts of small data and big data

Abstract

The differentiation between big data and small data is growing in confusion, in both academic and business domains. The confusion is endorsed by studies, by consistently arguing that the difference between big data and small data is not about size. The confusion between big data and small data is increasingly prohibitive for many organisations including students. As a result of the confusion and its associated implications, there are many costly decisions by individuals and groups in organisations. Consequently, productivity and quality of service are affected, which negatively reflect in competitiveness and sustainability. Thus, it is critically essential to address these growing challenges while the consequences are manageable. The objective of the study was to develop a taxonomy that distinguishes small data from big data, to remove the confusion, which often hinder understanding and affect the use for business enhancement. From the interpretivist approach perspective, the qualitative methods were employed in the study.