PREPARING BUSINESS ANALYSTS FOR THE MODERN JOB MARKET: A COMPARATIVE ANALYSIS OF SKILLS AND EDUCATION.
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| Title: | PREPARING BUSINESS ANALYSTS FOR THE MODERN JOB MARKET: A COMPARATIVE ANALYSIS OF SKILLS AND EDUCATION. |
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| Authors: | KOWALSKA-STYCZEC, Agnieszka, JUSZCZYK, Kinga |
| Source: | Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie; 2024, Issue 208, p215-231, 17p |
| Subject Terms: | BUSINESS skills, BUSINESS analytics, BUSINESS analysts, INTERPERSONAL communication, LABOR market |
| Abstract: | Purpose: To analyse and compare business analytics specializations in bachelor’s and engineering programs across selected Polish universities, focusing on the skill sets these programs emphasize to meet market demands. Design/methodology/approach: The study employed a comparative analysis of curricula across various institutions, organizing courses by primary skill categories: analytical, technical, communication, and project management skills. Findings: The research highlights distinct differences in focus between bachelor’s and engineering programs, with bachelor’s programs providing a broader skill base, including essential interpersonal and communication skills, while engineering programs emphasize technical and analytical expertise. Originality/value: This article provides insights into how business analytics education can be better aligned with market demands, offering a clear breakdown of specialization competencies that may guide curriculum development to address skill gaps in the profession. [ABSTRACT FROM AUTHOR] |
| Copyright of Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie is the property of Silesian Technical University, Organisation & Management Faculty and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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