Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework
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 analyt...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Australasian Association for Information Systems
2024-01-01
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| Series: | Australasian Journal of Information Systems |
| Subjects: | |
| Online Access: | https://journal.acs.org.au/index.php/ajis/article/view/4215 |
| _version_ | 1797339137254096896 |
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| author | Jia Xu Humza Naseer Sean Maynard Justin Filippou |
| author_facet | Jia Xu Humza Naseer Sean Maynard Justin Filippou |
| author_sort | Jia Xu |
| collection | DOAJ |
| description |
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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| first_indexed | 2024-03-08T09:41:34Z |
| format | Article |
| id | doaj.art-3c6fd322eb1e42da867e1521c9672c45 |
| institution | Directory Open Access Journal |
| issn | 1326-2238 |
| language | English |
| last_indexed | 2024-03-08T09:41:34Z |
| publishDate | 2024-01-01 |
| publisher | Australasian Association for Information Systems |
| record_format | Article |
| series | Australasian Journal of Information Systems |
| spelling | doaj.art-3c6fd322eb1e42da867e1521c9672c452024-01-30T05:37:06ZengAustralasian Association for Information SystemsAustralasian Journal of Information Systems1326-22382024-01-012810.3127/ajis.v28.4215Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual FrameworkJia Xu0Humza Naseer1Sean Maynard2Justin Filippou3University of MelbourneRMIT University Melbourne University of Melbourne University of Melbourne 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. https://journal.acs.org.au/index.php/ajis/article/view/4215Digital business transformationBusiness analyticsAnalytical information processing capabilityBoundary spanningDataOps |
| spellingShingle | Jia Xu Humza Naseer Sean Maynard Justin Filippou Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework Australasian Journal of Information Systems Digital business transformation Business analytics Analytical information processing capability Boundary spanning DataOps |
| title | Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework |
| title_full | Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework |
| title_fullStr | Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework |
| title_full_unstemmed | Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework |
| title_short | Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework |
| title_sort | using analytical information for digital business transformation through dataops a review and conceptual framework |
| topic | Digital business transformation Business analytics Analytical information processing capability Boundary spanning DataOps |
| url | https://journal.acs.org.au/index.php/ajis/article/view/4215 |
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