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arXiv 2201.09617cs.CY
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通过DataOps利用数据和分析实现数字化业务转型:信息处理视角

Leveraging Data and Analytics for Digital Business Transformation through DataOps: An Information Processing Perspective

Jia Xu, Humza Naseer, Sean Maynard, Justin Fillipou

摘要:

数字化业务转型对企业来说变得越来越重要。由于业务数字化转型是一个持续的过程,因此需要采用综合和规范的方法。实践中出现的数据运营(DataOps)可以为组织提供这样一种方法来利用数据和分析进行数字化业务转型。本文提出了一个框架,通过信息处理理论(IPT)的镜头集成数字化业务转型,数据分析和DataOps。该框架的细节解释了组织如何将DataOps作为一种集成和规范的方法来了解其分析信息需求,并开发数字业务转型所需的分析信息处理能力。反过来,支持DataOps的数字业务转型通过提高运营效率和创建新的业务模式来提高组织绩效。这项研究通过IPT引入DataOps和分析,扩展了当前对数字化转型的认识,从而为组织提供了一种新的数字化业务转型方法。

英文摘要:

Digital business transformation has become increasingly important for organizations. Since transforming business digitally is an ongoing process, it requires an integrated and disciplined approach. Data Operations (DataOps), emerging in practice, can provide organizations with such an approach to leverage data and analytics for digital business transformation. This paper proposes a framework that integrates digital business transformation, data analytics, and DataOps through the lens of information processing theory (IPT). The details of this framework explain how organizations can employ DataOps as an integrated and disciplined approach to understand their analytical information needs and develop the analytical information processing capability required for digital business transformation. DataOps-enabled digital business transformation, in turn, improves organizational performance by improving operational efficiency and creating new business models. This research extends current knowledge on digital transformation by bringing in DataOps and analytics through IPT and thereby provide organizations with a novel approach for their digital business transformations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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