The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Tools and Technologies Utilized in Data-Related Positions: An Empirical Study of Job Advertisements
Open accessAbstract
Role, value and amount of data and related tools, technologies, companies and professions in society is rising. Since the required skills for data-related professions are predicted to experience changes, and labor market mismatches create challenges for stakeholders, this research focuses on changes in the required tools and technologies for data-related positions. The presented research defines trends and changes in frequencies of the tools utilized in the data-related professions by applying quantitative content analysis on collected data from job advertisements of Finland, Denmark and Poland. The research findings show that tools used in data-related professions experience significant changes over time. For example, AI and cloud computing-related skills, and SQL started to be required more, whereas Excel, SPSS and similar tools are less expected from the candidates. Furthermore, while R programming language utilization rises in analytics related positions, Python is more common in positions related to data science.
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“Recent studies and reports indicate the presence of a skill gap across different professions [1,2]”
From Exploring the Impact of AI Tools on Cognitive Skills: A Comparative Analysis (2025) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“even though hard skills, such as programming languages and tools, remain essential for functionality.”
From Exploring the Impact of AI Tools on Cognitive Skills: A Comparative Analysis (2025) · cites this paper as [1]
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“A review of the literature [1] highlights that teamwork, communication, and domain knowledge are some of the key skills for emerging data-related professions”
From Exploring the Impact of AI Tools on Cognitive Skills: A Comparative Analysis (2025) · cites this paper as [1]
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Cites
Content Analysis: A Flexible Methodology
White, M. D., & Marsh, E. (2006) · Library trends · doi:10.1353/lib.2006.0053 · Cited by 2,335
Mauro, A. D., Greco, M., Grimaldi, M., & Ritala, P. (2017) · Information Processing & Management · doi:10.1016/j.ipm.2017.05.004 · Cited by 372
Sheng, J., Amankwah‐Amoah, J., Khan, Z., & Wang, X. (2021) · British Journal of Management · doi:10.1111/1467-8551.12441 · Cited by 369 · cited 2×
“Furthermore, data volume has a continuous rising trend, which generates the need for usage of advanced tools that are capable of processing big data (Power & Heavin, 2017, Sheng et al., 2020, Kenett & Redman, 2019).”
BackgroundSkill Requirements in Big Data: A Content Analysis of Job Advertisements
Gardiner, A. B., Aasheim, C. L., Rutner, P., & Williams, S. P. (2017) · Journal of Computer Information Systems · doi:10.1080/08874417.2017.1289354 · Cited by 126
Verma, A., Yurov, K. M., Lane, P. L., et al. (2019) · Journal of Education for Business · doi:10.1080/08832323.2018.1520685 · Cited by 118
Employability skills: Profiling data scientists in the digital labour market
Smaldone, F., Ippolito, A., Lagger, J., & Pellicano, M. (2022) · European Management Journal · doi:10.1016/j.emj.2022.05.005 · Cited by 112
Key competencies for big data analytics professions: a multimethod study
Persaud, A. (2020) · Information Technology and People · doi:10.1108/itp-06-2019-0290 · Cited by 96
Collaborative Approaches Needed to Close the Big Data Skills Gap
Miller, S. (2014) · Journal of Organization Design · doi:10.7146/jod.9823 · Cited by 89
Decision Support, Analytics, and Business Intelligence
Power, D. (2013) · UNI ScholarWorks (University of Northern Iowa) · doi:10.4128/9781606496190 · Cited by 56
Macnamara, J. (2018) · De Gruyter eBooks · doi:10.1515/9783110481129-012 · Cited by 47
Kenett, R. S., & Redman, T. C. (2019) · Wiley eBooks · doi:10.1002/9781119570790 · Cited by 40
Construing the big data based on taxonomy, analytics and approaches
Pathak, A. R., Pandey, M., & Rautaray, S. S. (2018) · Iran Journal of Computer Science · doi:10.1007/s42044-018-0024-3 · Cited by 30
Developing Analytic Talent: Becoming a Data Scientist
Granville, V. (2014) · Cited by 28
Data Science Skills and Graduate Certificates: A Quantitative Text Analysis
Jiang, H., & Chen, C. (2021) · Journal of Computer Information Systems · doi:10.1080/08874417.2020.1852628 · Cited by 15
A Multi-criteria Group Decision Making Method for Big Data Storage Selection
Kachaoui, J., & Belangour, A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-31277-0_25 · Cited by 12
Skill Requirements Analysis for Data Analysts Based on Named Entities Recognition
Cao, L., & Zhang, J. (2021) · International Conference on Big Data and Informatization Education (ICBDIE) · doi:10.1109/icbdie52740.2021.00023 · Cited by 10
A Multi-criteria Group Decision Making Method for Selecting Big Data Visualization Tools
Grandhi, S., & Wibowo, S. (2018) · Journal of Telecommunication Electronic and Computer Engineering (JTEC) · Cited by 7
A Study on Recruitment of Data Analyst Based on Text Mining and Visualization Technology
Fang, F., & Zhou, Y. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1952/4/042017 · Cited by 7
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Research works printed but not linked: 2
- Marr, B. (2019). Artificial intelligence in practice: How 50 successful companies used artificial intelligence to solve problems (First Edition). Wiley.
- https://doi.org/10.1108/itp-06-2019-0290 · DOI
Cited by
Sorted by citations
Exploring the Impact of AI Tools on Cognitive Skills: A Comparative Analysis
Musazade, N., Mezei, J., & Wang, X. (2025) · Algorithms · doi:10.3390/a18100631 · Cited by 10
“Recent studies and reports indicate the presence of a skill gap across different professions [1,2], with technological advancements considered one of the main causes of changing demand [3,4].”
Self-citation
Metadata
- Authors
- Musazade, N.
- Affiliations
- Åbo Akademi University (FI)
- Corresponding author
- Musazade, Nurlan
- ORCID
- Musazade, Nurlan
- Venue
- 36th Bled eConference – Digital Economy and Society: The Balancing Act for Digital Innovation in Times of Instability: June 25 – 28, 2023, Bled, Slovenia, Conference Proceedings
- Publisher
- University of Maribor Press
- Published
- 2023-12-12
- Pages
- 155-170
- OpenAlex
- W4389625879
- Cited by
- 3
- References
- 19
- Citations by year
- 2025: 1 · 2024: 2
- FWCI
- 0.77
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Bled eConference (publishedVersion, cc-by)
- Åbo Akademi University Research Portal (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Systems Education and Curriculum Development
- Social Sciences › Education › Higher Education and Employability
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Keywords
- job advertisements, skill requirements, labor market mismatch, data science, data analytics, programming languages, R programming language, Python, SQL, cloud computing, AI competencies, Microsoft Excel, SPSS
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