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.
Against this background, researchers at the Institute of Information Systems have conducted 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 analysing and interpreting the statistical results of the LSA, they developed a competency taxonomy for big data and business intelligence. The major findings are that
- business knowledge is as important as technical skills for working successfully on BI and BD initiatives
- BI competency is characterised by skills related to commercial products of large software vendors, whereas BD jobs ask for strong software development and statistical skills
- the demand for BI competencies is still far bigger than the demand for BD competencies
- BD initiatives are currently much more human-capital-intensive than BI projects are
The findings, which have been published in Business & Information Systems Engineering, can guide individual professionals, organisations, and academic institutions in assessing and advancing their BD and BI competencies.
