A process assessment model for big data analytics

2022-03-01
© 2021Today, business success is essentially powered by data-centric software. Big data analytics (BDA) grasp the potential of generating valuable insights and empowering businesses to support their strategic decision-making. However, although organizations are aware of BDAs’ potential opportunities, they face challenges to satisfy the BDA-specific processes and integrate them into their daily software development lifecycle. Process capability/ maturity assessment models are used to assist organizations in assessing and realizing the value of emerging capabilities and technologies. However, as a result of the literature review and its analysis, it was observed that none of the existing studies in the BDA domain provides a complete, standardized, and objective capability maturity assessment model. To address this research gap, we focus on developing a BDA process capability assessment model grounded on the well-accepted ISO/IEC 330xx standard series. The proposed model comprises two main dimensions: process and capability. The process dimension covers six BDA-specific processes: business understanding, data understanding, data preparation, model building, evaluation, and deployment and use. The capability dimension has six levels, from not performed to innovating. We conducted case studies in two different organizations to validate the applicability and usability of the proposed model. The results indicate that the proposed model provides significant insights to improve the business value generated by BDA via determining the current capability levels of the organizations' BDA processes, deriving a gap analysis, and creating a comprehensive roadmap for continuous improvement in a standardized way.
Computer Standards and Interfaces
Citation Formats
M. O. Gökalp, E. Gökalp, K. Kayabay, S. Gökalp, A. Koçyiğit, and P. E. Eren, “A process assessment model for big data analytics,” Computer Standards and Interfaces, vol. 80, pp. 0–0, 2022, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93801.