Big Data Analysis for Predicting Future Skills

A. Telukdarie; M. Munsamy; M. Gaula

doi:10.1109/IEEM50564.2021.9673039

Big Data Analysis for Predicting Future Skills

Johannesburg Business School

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

The ability to predict skills of the future is fundamental in this rapidly changing global environment. The ability to predict and invest in the appropriate skills could prove to be a key differentiator for country specific growth. Global competitiveness, employment, technological investments, and social-economic dependencies are drivers to capacity development to predict future skills. The current approaches include a combination of expanding on current skill demand, adoption of economic indicators or survey-based forecasting. The challenge is the inclusion of future trends, specifically the ability to forecast new skills or combinations of existing skills. This research explores a novel method in adopting research publications to predict new/ undetermined skills requirements. This study downloads 700 000 papers, develops a multilayer data analysis protocol, screens and provides insights into the adoption of research publications analysis for the prediction of future skills.

Original language	English
Title of host publication	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	411-415
Number of pages	5
ISBN (Electronic)	9781665437714
DOIs	https://doi.org/10.1109/IEEM50564.2021.9673039
Publication status	Published - 2021
Event	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 - Virtual, Online, Singapore Duration: 13 Dec 2021 → 16 Dec 2021

Publication series

Name	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

Conference

Conference	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Country/Territory	Singapore
City	Virtual, Online
Period	13/12/21 → 16/12/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education

Keywords

Digital
Skills prediction

ASJC Scopus subject areas

Strategy and Management
Artificial Intelligence
Computer Science Applications
Information Systems and Management
Industrial and Manufacturing Engineering
Control and Optimization

Access to Document

10.1109/IEEM50564.2021.9673039

Cite this

Telukdarie, A., Munsamy, M., & Gaula, M. (2021). Big Data Analysis for Predicting Future Skills. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 (pp. 411-415). (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEEM50564.2021.9673039

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title = "Big Data Analysis for Predicting Future Skills",

abstract = "The ability to predict skills of the future is fundamental in this rapidly changing global environment. The ability to predict and invest in the appropriate skills could prove to be a key differentiator for country specific growth. Global competitiveness, employment, technological investments, and social-economic dependencies are drivers to capacity development to predict future skills. The current approaches include a combination of expanding on current skill demand, adoption of economic indicators or survey-based forecasting. The challenge is the inclusion of future trends, specifically the ability to forecast new skills or combinations of existing skills. This research explores a novel method in adopting research publications to predict new/ undetermined skills requirements. This study downloads 700 000 papers, develops a multilayer data analysis protocol, screens and provides insights into the adoption of research publications analysis for the prediction of future skills.",

keywords = "Digital, Skills prediction",

author = "A. Telukdarie and M. Munsamy and M. Gaula",

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language = "English",

series = "2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021",

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address = "United States",

}

Telukdarie, A , Munsamy, M & Gaula, M 2021, Big Data Analysis for Predicting Future Skills. in 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021, Institute of Electrical and Electronics Engineers Inc., pp. 411-415, 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021, Virtual, Online, Singapore, 13/12/21. https://doi.org/10.1109/IEEM50564.2021.9673039

Big Data Analysis for Predicting Future Skills. / Telukdarie, A.; Munsamy, M.; Gaula, M.
2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 411-415 (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Big Data Analysis for Predicting Future Skills

AU - Telukdarie, A.

AU - Munsamy, M.

AU - Gaula, M.

PY - 2021

Y1 - 2021

N2 - The ability to predict skills of the future is fundamental in this rapidly changing global environment. The ability to predict and invest in the appropriate skills could prove to be a key differentiator for country specific growth. Global competitiveness, employment, technological investments, and social-economic dependencies are drivers to capacity development to predict future skills. The current approaches include a combination of expanding on current skill demand, adoption of economic indicators or survey-based forecasting. The challenge is the inclusion of future trends, specifically the ability to forecast new skills or combinations of existing skills. This research explores a novel method in adopting research publications to predict new/ undetermined skills requirements. This study downloads 700 000 papers, develops a multilayer data analysis protocol, screens and provides insights into the adoption of research publications analysis for the prediction of future skills.

AB - The ability to predict skills of the future is fundamental in this rapidly changing global environment. The ability to predict and invest in the appropriate skills could prove to be a key differentiator for country specific growth. Global competitiveness, employment, technological investments, and social-economic dependencies are drivers to capacity development to predict future skills. The current approaches include a combination of expanding on current skill demand, adoption of economic indicators or survey-based forecasting. The challenge is the inclusion of future trends, specifically the ability to forecast new skills or combinations of existing skills. This research explores a novel method in adopting research publications to predict new/ undetermined skills requirements. This study downloads 700 000 papers, develops a multilayer data analysis protocol, screens and provides insights into the adoption of research publications analysis for the prediction of future skills.

KW - Digital

KW - Skills prediction

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M3 - Conference contribution

AN - SCOPUS:85125379841

T3 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

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EP - 415

BT - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Telukdarie A , Munsamy M, Gaula M. Big Data Analysis for Predicting Future Skills. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 411-415. (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021). doi: 10.1109/IEEM50564.2021.9673039

Big Data Analysis for Predicting Future Skills

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this