Bridging Competency Gaps in Data Science: Evaluating the Role of Automation Frameworks Across the DASC-PM Lifecycle

Maike Holtkemper, Christian Beecks

2025

Abstract

Successful data science projects require a balanced mix of competencies. However, a shortage of skilled professionals disrupts this balance, fragmenting expertise across the data science pipeline. This fragmentation causes inefficiencies, delays, and project failures. Automation frameworks can help to mitigate these issues by handling repetitive tasks and integrating specialized skills. These frameworks improve workflow efficiency across project phases but remain limited in critical areas like project initiation and deployment. This pre-study identifies tasks in each project phase using the DASC-PM model. The model structures the assessment of automation potential and maps tasks to the EDISON Data Science Framework (EDSF), determining which competencies automation can support. The findings indicate that automation enhances efficiency in early phases, such as Data Provision and Analysis, contrasting with challenges in Project Order and Deployment, where human expertise remains essential. Addressing these gaps can improve collaboration and create a more integrated data science workflow.

Paper Citation

in Harvard Style

Holtkemper M. and Beecks C. (2025). Bridging Competency Gaps in Data Science: Evaluating the Role of Automation Frameworks Across the DASC-PM Lifecycle. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 491-499. DOI: 10.5220/0013559900003967

in Bibtex Style

@conference{data25,
author={Maike Holtkemper and Christian Beecks},
title={Bridging Competency Gaps in Data Science: Evaluating the Role of Automation Frameworks Across the DASC-PM Lifecycle},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={491-499},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013559900003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Bridging Competency Gaps in Data Science: Evaluating the Role of Automation Frameworks Across the DASC-PM Lifecycle
SN - 978-989-758-758-0
AU - Holtkemper M.
AU - Beecks C.
PY - 2025
SP - 491
EP - 499
DO - 10.5220/0013559900003967
PB - SciTePress