Recently, augmented analytics has increasingly gained attention as one of the more advanced, novel approaches for handling big data. Based on machine learning and natural language processing, augmented analytics benefits from recent advancements in the artificial intelligence field to automate the analytics cycle. Despite the various benefits that augmented analytics offers for business and society, research on this topic is scarce to date. Based on the IT business value model, we examine the role of technological and social resources as well as the main use cases of augmented analytics. Therefore, we combine quantitative text mining with qualitative content analysis for an exploratory study of 350 academic and practical publications as well as 49 datasets of companies offering augmented analytics software and services. The findings contribute to the body of knowledge by enhancing the understanding of the augmented analytics concept, uncovering prevalent research gaps, and highlighting future research directions.
Oesterreich, Thuy Duong; Anton, Eduard; and Xu, Feipeng, "Augmenting the Future: An Exploratory Analysis of the Main Resources, Use Cases and Implications of Augmented Analytics" (2021). ECIS 2021 Research Papers. 19.
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