Technology factors required for adopting cloud-based big data analytics in South African banking - A. P. Msweli; T. R. Seaba; V. N. Paledi; K. Sigama (International Journal of Science Annals)
Background and Aim of Study: South African banks are generally known for early technology adoption. While this is so, there is a need to integrate some of the fourth industrial revolution technologies such as big data analytics and cloud computing collectively referred to as cloud-based big data analytics; and subsequently consider technology related aspects required for adopting integrated technologies of this nature. The aim of the study is to identify technology related factors that are necessary for adopting cloud-based big data analytics in South African banking. Material and Methods: A qualitative research approach was followed as well as an interpretivism paradigm and a single case study research strategy. Semi-structured interviews were employed for data collection from eleven professionals in the Information Technology division of a South African bank. Results: In total, 35 technology factors required for adopting cloud-based big data analytics were identified in this study and furthermore categorized into; internal cloud-based big data analytics criteria, cloud-based big data analytics capabilities or skills, cloud-based big data analytics data integrity levels, data security and readiness for adopting cloud-based big data analytics and cloud-based big data analytics external criteria. Conclusions: The results of this study could imply that the adoption of cloud-based big data analytics in the banking sector takes into consideration an outsourcing model or setting. In this structure, technology factors are not only specific to the bank concerned. The banking sector has its own technology requirements that banks are expected to adhere to or take into consideration, while some technology factors could only be addressed by the cloud-based big data analytics service providers. The identified factors could be used in the conceptualization of a cloud-based big data analytics framework in future research.