Human interaction with structure in designing big data architecture

Abstract

Background: There is an increasing interest in big data. However, challenges shape and affect the gathering, retrieval, use and management of big data in many organisations. Some of the challenges are linked to a lack of architecture that is specific to big data. Attempts have been made from both business and academic fronts, yet the challenges persist. The challenges are attributed to a lack of an understanding of the factors that influence the design of architecture for big data in an organisation.

Objectives: The study aims to propose big data architecture for enterprises.

Method: We employed the qualitative method, using document analysis to gather data. Activity theory (AT) was employed in the analysis of the data.

Results: From the analysis, governance, interactions, relationships and allocative were found to be the factors that influence the design of big data architecture. An interpretation was conducted following the inductive reasoning approach to gain a deeper insight of how the factors manifest themselves.

Conclusion: Big data architecture is proposed. The architecture is intended to address some of the challenges encountered in gathering, retrieving, using or managing big data in organisations.

Contribution: This study advances our understanding of the complex interplay of factors influencing the architecture of big data. Applying AT, the study fortifies our understanding of complex interactions between humans and big data including the architecture design.