Increased proliferation of new data sets and the persistent desire to stay ahead of the competition has compelled organizations to harness business analytics (BA) to drive strategic business decisions. However, issues such as the lack of collaboration among stakeholders, poor data quality, and slow delivery times are inhibiting the ability of organizations to utilize BA capability for making datadriven decisions in an agile manner. Data operations (DataOps), an emerging discipline, is believed to have the potential to modernize the BA capablity in such way to improve collaboration, data quality and accelrate delivery times, thereby enhancing the speed and accuracy of data-driven decisions. The goal of this on-going study is to examine how organizations can modernize their BA capability by employing DataOps. We propose a theoretical framework that explains how key components of BA capability (people, process, technology, and organization) are impacted by DataOps and how BA capability enabled by DataOps improves decision-making agility. We plan to: a) conduct expert interviews with BA professionals involved in DataOps implementations in both the consulting and corporate domains and b) conduct multiple in-depth case studies with organizations that have matured in their practice of DataOps to explain how DataOps modernizes BA capability.
Naseer, Humza; Maynard, Sean B.; and Xu, Jia, "Modernizing business analytics capability with DataOps: A decision-making agility perspective" (2020). ECIS 2020 Research-in-Progress Papers. 36.
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