Analysis of Relationships Between Business Domains and Technical-Skill Requirements for Data Analysts

As growth of the data analytics field continues, more and more academic departments and professional training programs are offering skill training to potential data analysts. However, not all business domains require their data analysts to possess the same sets of technical skills. Based on over 2,5...

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Veröffentlicht in:Journal of global information management Jg. 32; H. 1; S. 1 - 20
Hauptverfasser: Le, Taowen, Zhang, Jin, Chen, Jianyao, Zhao, Yiming
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hershey IGI Global 01.01.2024
Schlagworte:
Academic departments
Advertisements
Advertising
Analysts
Business
Business analytics
Data
Data analysis
Decision making
Educational programs
Industry 4.0
Information management
Job qualifications
Job vacancies
Literature reviews
Personnel selection
Professional training
Researchers
Scientific visualization
Skill development
Skills
Social networks
Specialization
Structured Query Language-SQL
Students
Tabulation
Teachers
Technical skills
Training
Vocational qualifications
Work skills
ISSN:1062-7375, 1533-7995
Online-Zugang:Volltext
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Zusammenfassung:As growth of the data analytics field continues, more and more academic departments and professional training programs are offering skill training to potential data analysts. However, not all business domains require their data analysts to possess the same sets of technical skills. Based on over 2,500 data-analyst job advertisements posted on LinkedIn and utilizing subject analysis, cross-tabulation analysis, heat map, Kruskal-Wallis test, and Kappa test, this study examined relationships between various business domains and the technical skills required for data analysts within the respective business domains. Among many findings, the study discovered noteworthy disparities among the business domains concerning their requirements of technical-skill sets for data analysts. The findings of this study offer valuable insights to educators and potential data analysts.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1062-7375
1533-7995
DOI:10.4018/JGIM.357276