Critical success factor categories for big data: A preliminary analysis of the current academic landscape

Big Data (BD) is a popular talking point currently. Companies invest huge amounts of resources to manage and maintain Big Data with mixed results. Understanding the Critical Success Factors (CSFs) associated with the successful management and maintenance of BD can aid organisations to obtain higher returns on their investment. This study focused on the identification of Critical Success Factors (CSFs) categories published in academic journals and conference proceedings on the topic of Big Data. It adopted a qualitative approach to classify the factors into categories and proposes a high level, preliminary model of CSF categorization. The model postulates that CSFs can be classified in three main categories namely Organisational, People and Technology. These categories can be used in future studies to test for the applicability and utilisation of BD by organisations. Furthermore, the authors postulate that the CSFs for all three categories should prevail in order to achieve the maximum value and success of BD implementations. The study also indicated that further research is necessary to refine the classification by considering alternative frameworks such as BD capability frameworks.