Activity theory view of big data architectural design for enterprises

Abstract

The lack of architectural design leads to the fragmentation of big data and increases the complexity of an environment. This study aims to develop big data architectural design for enterprises. The qualitative method was employed, and literature relating to the study was gathered and examined. Heuristically, the data was analysed, which was guided by the activity theory (AT) as a lens. From the analysis, relationship, allocative, and interaction were found to be the fundamental factors influencing big data architectural design. Additionally, the study highlights the attributes of the factors, which include technology, governance, and transformation. Based on the factors and their attributes, a big data architectural design was developed. The proposed big data architectural design has significant implications for improving the efficiency and effectiveness of an enterprise’s processes, services, and competitiveness. However, there are implications and limitations. From both information technology (IT) and business units’ standpoints, the study highlights operationalisation, innovation, and integration as implications for enterprises. Non-empirical evidence is a limitation which should be considered for future studies.