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Investigating the data science skill gap: An empirical analysis

Mikalef, Patrick; Krogstie, John
Peer reviewed, Journal article
Accepted version
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Mikalef (279.8Kb)
URI
https://hdl.handle.net/11250/2758210
Date
2019
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  • Institutt for datateknologi og informatikk [4881]
  • Publikasjoner fra CRIStin - NTNU [26591]
Original version
IEEE Global Engineering Education Conference, EDUCON. 2019, April-2019 1275-1284.   10.1109/EDUCON.2019.8725066
Abstract
With big data analytics constantly growing in importance for contemporary organizations so does the need for skilled professionals. Perhaps the most critical item noted in the age of data is the lack of people with the required skill-set to turn raw data into actionable insight. Building on this pressuring issue, the objective of this paper is to survey the status quo of technical and businessrelated data analytics skills in a range of different industries and identify the most important skills that will be needed in the next few years. To do so, this study builds on a sample of 202 survey responses from key executives from Norwegian firms. Our analysis reveals the level of skill-fulfilment in for technically and business-oriented employees in a number of key industries. In addition, we use survey data from an additional sample of 27 executives and interviews with 6 managers and provide a ranking of the perceived importance of data analytics-related skills according to respondents in three categories, technical skills, business and project management skills, and soft skills. Our study concludes with findings regarding the skill-gap that exists in the domain of data science as well as suggestions on how to fulfil these needs, indicating specific subject-areas that are of heightened importance.
Publisher
IEEE
Journal
IEEE Global Engineering Education Conference, EDUCON

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