Big Data Analytics Adoption Framework and its Verification Using a Case Study

Many organizations are in the process of adopting big data analytics (BDA) to make data driven decisions. In this work, we have used a variant of CRISP-DM and broken-down processes into sub-processes, meanwhile also integrating critical success factors in the framework. We have validated our framework to understand BDA adoption via a case study of a big data analytics firm, referred to as ABC in this study. ABC helps large farmers to make farming decisions based on BDA. We conducted in-depth interviews with the Data science team of ABC to validate our framework. In terms of critical success factors, costing, project planning, adoption strategy, identification of business problems, project team formation, data management, training, change management and final preparation were identified as important by ABC for BDA projects. In addition, ABC also considers maintenance, evaluation of business objectives and overall project management critical that were not part of our model. We have incorporated these in our framework. Our research contributes to the growing body of knowledge on BDA adoption, offering valuable insights specific to the agricultural sector and emphasizing the challenges and opportunities posed by the substantial volume and variety of data in this domain.