Seventeenth International Conference on Technology, Knowledge, and Society

Abstract

Rapidly expanding automation is not only reshaping how work is done – it is changing the very essence of economic value creation, and by extension, the makeup of core business competencies. Torrents of data spawned by the ever-expanding electronic transactional and communication infrastructure hide enormous informational potential, but tapping into it requires specialized skillset. Not surprisingly, data analytic literacy joins communication, teamwork, and critical thinking as an essential business competency, which means that to be positioned to contribute to, and benefit from the emerging Age of Data opportunities, business (and other) graduates need to be analytically literate. Development of data analytic literacy, however, calls for more than adding a handful of ‘data courses’ – what is needed is a comprehensive approach focused on learning how to translate a variety of messy and dissimilar data streams into decision-guiding knowledge. In other words, there is an urgent need to infuse university curricula with data utilization competencies, framed here as data analytic literacy. An important aspect of data analytic literacy is that it is a multidisciplinary competency that combines elements of computer science, statistics, cognitive sciences, and management, in a way that facilitates infusion of objective data derived insights into traditionally subjective reasoning driven decision-making. In an operational sense, it entails a lot more than just ‘data crunching’ – fully developed data analytic literacy can be characterized as the ability to learn with data in a manner that cognitively resembles learning from experience.