Leveraging XP and CRISP-DM for Agile Data Science Projects
May 27, 2025 Β· Declared Dead Β· π European Journal of Electrical Engineering and Computer Science
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Authors
Andre Massahiro Shimaoka, Renato Cordeiro Ferreira, Alfredo Goldman
arXiv ID
2505.21603
Category
cs.SE: Software Engineering
Cross-listed
cs.AI,
cs.LG
Citations
0
Venue
European Journal of Electrical Engineering and Computer Science
Last Checked
5 months ago
Abstract
This study explores the integration of eXtreme Programming (XP) and the Cross-Industry Standard Process for Data Mining (CRISP-DM) in agile Data Science projects. We conducted a case study at the e-commerce company Elo7 to answer the research question: How can the agility of the XP method be integrated with CRISP-DM in Data Science projects? Data was collected through interviews and questionnaires with a Data Science team consisting of data scientists, ML engineers, and data product managers. The results show that 86% of the team frequently or always applies CRISP-DM, while 71% adopt XP practices in their projects. Furthermore, the study demonstrates that it is possible to combine CRISP-DM with XP in Data Science projects, providing a structured and collaborative approach. Finally, the study generated improvement recommendations for the company.
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