Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework


  • Jia Xu University of Melbourne
  • Humza Naseer RMIT University Melbourne
  • Sean Maynard University of Melbourne
  • Justin Filippou University of Melbourne



Digital business transformation, Business analytics, Analytical information processing capability, Boundary spanning, DataOps


Organisations are increasingly practising business analytics to generate actionable insights that can guide their digital business transformation. Transforming business digitally using business analytics is an ongoing process that requires an integrated and disciplined approach to leveraging analytics and promoting collaboration. An emerging business analytics practice, Data Operations (DataOps), provides a disciplined approach for organisations to collaborate using analytical information for digital business transformation. We propose a conceptual framework by reviewing the literature on business analytics, DataOps and organisational information processing theory (OIPT). This conceptual framework explains how organisations can employ DataOps as an integrated and disciplined approach for developing the analytical information processing capability and facilitating boundary-spanning activities required for digital business transformation. This research (a) extends current knowledge on digital transformation by linking it with business analytics from the perspective of OIPT and boundary-spanning activities, and (b) presents DataOps as a novel approach for using analytical information for digital business transformation.


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How to Cite

Xu, J., Naseer, H., Maynard, S., & Filippou, J. . (2024). Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework. Australasian Journal of Information Systems, 28.



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