Skills and Competencies Required for Jobs in Business Analytics: A Content Analysis of Job Advertisements Using Text Mining

Linda A. Leon, Kala Chand Seal, Zbigniew H. Przasnyski and Ian Wiedenman
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Linda A. Leon: Department of Finance and Computer Information Systems, Loyola Marymount University, Los Angeles, CA, USA
Kala Chand Seal: Department of Finance and Computer Information Systems, Loyola Marymount University, Los Angeles, CA, USA
Zbigniew H. Przasnyski: Department of Finance and Computer Information Systems, Loyola Marymount University, Los Angeles, CA, USA
Ian Wiedenman: Loyola Marymount University, Los Angeles, CA, USA

International Journal of Business Intelligence Research (IJBIR), 2017, vol. 8, issue 1, 1-25

Abstract: The explosive growth of business analytics has created a high demand for individuals who can help organizations gain competitive advantage by extracting business knowledge from data. What types of jobs satisfy this demand and what types of skills should individuals possess to satisfy this huge and growing demand? The authors perform a content analysis of 958 job advertisements posted during 2014-2015 for four types of positions: business analyst, data analyst, data scientist, and data analytics manager. They use a text mining approach to identify the skills needed for these job types and identify six distinct broad competencies. They also identify the competencies unique to a particular type of job and those common to all job types. Their job type categorization provides a framework that organizations can use to inventory their existing workforce competencies in order to identify critical future human resources. It can also guide individual professionals with their career planning as well as academic institutions in assessing and advancing their business analytics curricula.

Date: 2017
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