Comparing Business Intelligence and Big Data Skills

Stefan Debortoli (), Oliver Müller () and Jan Brocke ()
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Stefan Debortoli: http://www.uni.li/iwi

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2014, vol. 6, issue 5, 289-300

Abstract: While many studies on big data analytics describe the data deluge and potential applications for such analytics, the required skill set for dealing with big data has not yet been studied empirically. The difference between big data (BD) and traditional business intelligence (BI) is also heavily discussed among practitioners and scholars. We conduct a latent semantic analysis (LSA) on job advertisements harvested from the online employment platform monster.com to extract information about the knowledge and skill requirements for BD and BI professionals. By analyzing and interpreting the statistical results of the LSA, we develop a competency taxonomy for big data and business intelligence. Our major findings are that (1) business knowledge is as important as technical skills for working successfully on BI and BD initiatives; (2) BI competency is characterized by skills related to commercial products of large software vendors, whereas BD jobs ask for strong software development and statistical skills; (3) the demand for BI competencies is still far bigger than the demand for BD competencies; and (4) BD initiatives are currently much more human-capital-intensive than BI projects are. Our findings can guide individual professionals, organizations, and academic institutions in assessing and advancing their BD and BI competencies. Copyright Springer Fachmedien Wiesbaden 2014

Keywords: Big data; Business intelligence; Competencies; Latent semantic analysis; Text mining (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s12599-014-0344-2

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