<\/a><\/p>\n Marc A. Richly, Ludwig Maximilian University of Munich (Master thesis) While the amount of data keeps growing, managers ask themselves whether they already retrieve full value from their data. To maximize the value of big data, literature offers first insights in building BDA capabilities (Gupta and George 2016, p; Mikalef et al. 2018).\u00a0Nevertheless, BDA remains a new field to researchers and companies. BDA frameworks, still offered scarcely, discuss roughly the same dimensions (incorporating some technical, human, and cultural aspects), but are only superficially discussed. This thesis builds a framework of the different approaches offered in literature.\u00a0Furthermore, it is important to distinguish whether a new development as BDA can be seen as a trend topic or rather a long-lasting game changer for businesses.\u00a0Here, this thesis discusses differences among digital capabilities, IT capabilities, that research stared addressing by 1990, and BDA capabilities. A major finding is that building IT capabilities is considered as an isolated responsibility of IT departments by, i.e., offering IT infrastructure to the whole company. BDA capabilities, on the contrary, cannot be planned and rolled out from one specific department \u2013 those need to be developed in every organizational unit; therefore, a data-driven culture is a key element in building BDA capabilities. Keywords: Big data analytics; Big data; Data analytics; Dynamic capabilities; Resource-based view.<\/span><\/em><\/p>\n<\/div>Big Data Analytics Capabilities: A Systematic Literature Review on Necessary Skills to Succeed in Big Data Analytics<\/h5>\n
\nJunior Management Science 7(5), 2022, 1224-1241<\/p>\n<\/div><\/i><\/i><\/span>Read abstract<\/span><\/a><\/h4><\/div>
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