Comparative Analysis of Process Models for Data Science Projects

Damian Kutzias, Claudia Dukino, Falko Kötter, Holger Kett

2023

Abstract

When adopting data science technology into practice, enterprises need proper tools and process models. Data science process models guide the project management by providing workflows, dependencies, requirements, relevant challenges and questions as well as suggestions of proper tools for all tasks. Whereas process models for classic software development have evolved for a comparably long time and therefore have a high maturity, data science process models are still in rapid evolution. This paper compares existing data science process models using literature analysis, and identifies the gap between existing models and relevant challenges by performing interviews with experts.

Paper Citation

in Harvard Style

Kutzias D., Dukino C., Kötter F. and Kett H. (2023). Comparative Analysis of Process Models for Data Science Projects. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 1052-1062. DOI: 10.5220/0011895200003393

in Bibtex Style

@conference{icaart23,
author={Damian Kutzias and Claudia Dukino and Falko Kötter and Holger Kett},
title={Comparative Analysis of Process Models for Data Science Projects},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={1052-1062},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011895200003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Comparative Analysis of Process Models for Data Science Projects
SN - 978-989-758-623-1
AU - Kutzias D.
AU - Dukino C.
AU - Kötter F.
AU - Kett H.
PY - 2023
SP - 1052
EP - 1062
DO - 10.5220/0011895200003393