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Emerging trends in data analytics and knowledge management job market: extending KSA framework

Hsia-Ching Chang (College of Information, University of North Texas, Denton, Texas, USA)
Chen-Ya Wang (Department of Management and Information, National Open University, New Taipei City, Taiwan)
Suliman Hawamdeh (College of Information, University of North Texas, Denton, Texas, USA)

Journal of Knowledge Management

ISSN: 1367-3270

Article publication date: 15 November 2018

Issue publication date: 20 May 2019

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Abstract

Purpose

This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design.

Design/methodology/approach

This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM.

Findings

Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels.

Practical implications

The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula.

Originality/value

This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.

Keywords

Citation

Chang, H.-C., Wang, C.-Y. and Hawamdeh, S. (2019), "Emerging trends in data analytics and knowledge management job market: extending KSA framework", Journal of Knowledge Management, Vol. 23 No. 4, pp. 664-686. https://doi.org/10.1108/JKM-02-2018-0088

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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