A decision support framework for selecting big data analytics tools in an organisation

Abstract

The objectives of this study were to gain an understanding into the factors that influence the selection of big data analytics tools in organisations, and to formulate criteria that can guide the selection of big data analytics tools in an organization. Based on the understanding of the factors and criteria, a decision support framework was proposed, to assist in the selection of big data analytics tools in an organisation. In achieving the aim and objectives of this study, a case study approach was employed, and developing countries was selected for the case of study. The qualitative methods and interpretive approach were used. Document analysis and semi-structured interviews were used to collect data. Actor-network theory was used to underpin the study. The approaches and methods were considered most appropriate in acquiring a deeper understanding of how organisations select, use and adopt big data analytics tools. In the analysis, the moments of translation from the perspective of actor-network theory were employed to focus on the actors, networks that influence the selection of big data analytics tools in organisations. From the analysis, it was discovered that there are five factors that influence the selection of big data analytics tools in an organisation, namely: Requirements, Approach: Top-down vs Bottom-up, Stakeholder Role, BDA Usefulness, and Organisational Structure. Subsequently, criteria that guide the selection of big data analytics were formulated and noted to be: Scalability, Functionality, Non-functionality, Technology, Ownership, Model, and Skill. Based on these findings a decision support framework for the selection of big data analytics tools in an organisation was proposed.