Facilitating transmuters' acquisition of data scientist knowledge based on their educational backgrounds

Facilitating transmuters' acquisition of data scientist knowledge based on their educational backgrounds: state-of-the-practice and challenges

Ramzan, Muhammad Javed (International Islamic University Islamabad)
Khan, Saif Ur Rehman (International Islamic University Islamabad)
ur-Rehman, Inayat (International Islamic University Islamabad)
Rehman, Muhammad Habib Ur (Khalifa University of Science and Technology)
Al-Khanak, Ehab Nabiel (TU Delft Transport and Planning)

2021

Purpose: In recent years, data science has become a high-demand profession, thereby attracting transmuters (individuals who want to change their profession due to industry trends) to this field. The primary purpose of this paper is to guide transmuters in becoming data scientists. Design/methodology/approach: An exploratory study was conducted to uncover the challenges faced by data scientists according to their educational backgrounds. An extensive set of responses from 31 countries was received. Findings: The results reveal that skill requirements and tool usage vary significantly with educational background. However, regardless of differences in academic background, the data scientists surveyed spend more time analyzing data than operationalizing insight. Research limitations/implications: The collected data are available to support replication in various scenarios, for example, for use as a roadmap for those with an educational background in art-related disciplines. Additional empirical studies can also be conducted specific to geographical location. Practical implications: The current work has categorized data scientists by their fields of study making it easier for universities and online academies to suggest required knowledge (courses) according to prospective students' educational background. Originality/value: The conducted study suggests the required knowledge and skills for transmuters to acquire, based on their educational background, and reports a set of motivational factors attracting them to adopt the data science field.

Challenges
Data science
Data scientist
Guidance
Motivational factors
Skillset
Tools

http://resolver.tudelft.nl/uuid:aef20c70-314f-49ef-92ec-ceb0137c11b7

https://doi.org/10.1108/LHT-08-2020-0203

0737-8831

Library Hi Tech, 41 (4), 1119-1144

Accepted Author Manuscript

Institutional Repository

journal article

© 2021 Muhammad Javed Ramzan, Saif Ur Rehman Khan, Inayat ur-Rehman, Muhammad Habib Ur Rehman, Ehab Nabiel Al-Khanak