Key competencies for big data analytics professions: a multimethod study

Abstract

PurposeThis study aims to identify the precise competencies that employers are seeking for big data analytics professions and whether higher education big data programs enable students to acquire the competencies.Design/methodology/approachThis study utilizes a multimethod approach involving three data sources: online job postings, executive interviews and big data programs at universities and colleges. Text mining analysis guided by a holistic competency theoretical framework was used to derive insights into the required competencies.FindingsWe found that employers are seeking workers with strong functional and cognitive competencies in data analytics, computing and business combined with a range of social competencies and specific personality traits. The exact combination of competencies required varies with job levels and tasks. Executives clearly indicate that workers rarely possess the competencies and they have to provide additional training.Research limitations/implicationsA limitation is our inability to capture workers' perspectives to determine the extent to which they think they have the necessary competencies.Practical implicationsThe findings can be used by higher educational institutions to design programs to better meet market demand. Job seekers can use it to focus on the types of competencies they need to advance their careers. Policymakers can use it to focus policies and investments to alleviate skills shortages. Industry and universities can use it to strengthen their collaborations.Social implicationsMuch closer collaborations among public institutions, educational institutions, industry, and community organizations are needed to ensure training programs evolve with the evolving need for skills driven by dynamic technological changes.Originality/valueThis is the first study on this topic to adopt a multimethod approach incorporating the perspectives of the key stakeholders in the supply and demand of skilled workers. It is the first to employ text mining analysis guided by a holistic competency framework to derive unique insights.

Understanding business analytics continuance in agile information system development projects: an expectation-confirmation perspective

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Personality in information systems professions: identifying archetypal professions with suitable traits and candidates' ability to fake-good these traits

“…Each of the proposed professions is attached to a unique personality type that matches the specific profession's identified characteristics along with a specific MBTI personality type. The set of characteristics that reflect the specific IS archetype were extracted from the literature (Kriegsman and Barletta, 1993;Todd et al, 1995;Marcella and Middleton, 1996;Wynekoop and Walz, 2000;Denning, 2001;Cappel, 2002;Noll and Wilkins, 2002;Kim et al, 2006;Lounsbury et al, 2007;Devaraj et al, 2008;Lee and Han, 2008;Aken et al, 2009;Litecky et al, 2009;Capretz and Ahmed, 2010;Varona et al, 2011;Aasheim et al, 2012;Davenport and Patil, 2012;Guillemette and Par e, 2012;Maier, 2012;Cohen et al, 2013;Summers et al, 2013;Van der Aalst, 2014;Flynn and Philbin, 2014;Kruck et al, 2014;Sackett and Walmsley, 2014;M€ uller et al, 2016;Pfl€ ugler et al, 2018;Mendes et al, 2019;Persaud, 2020). Then, each author assessed each characteristic individually.…”

Application of the global computing curriculum guidelines and skills frameworks for competency discovery and analysis: a case study of data analytics

“…A newer conception of competency is proposed by [17], namely, a holistic model expressed as "Competency = functional competence + cognitive competence + social competence + meta competence". The functional refers to the ability to perform a range of activities, achieve specific outcomes and demonstrate industry standards.…”