Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects

Jeffrey S. Saltz; Nicholas Hotz

doi:10.1109/BigData50022.2020.9377813

Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects

Jeffrey S. Saltz, Nicholas Hotz

School of Information Studies

Research output: Chapter in Book/Entry/Poem › Conference contribution

14 Scopus citations

Abstract

This paper presents the results of a study focused on exploring which framework, if any, teams use to execute data science projects. The study consisted of a survey of 109 industry professionals, as well as an evaluation of relevant framework terms searched at Google. Overall, CRISP-DM was the most commonly used framework, with Scrum and Kanban being the second and third most frequently used. We note that CRISP-DM is a life cycle framework, whereas Scrum and Kanban are team coordination frameworks. Hence, this research also notes the potential demand for a framework that integrates both life cycle and team coordination aspects of leading a data science project.

Original language	English (US)
Title of host publication	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
Editors	Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2038-2042
Number of pages	5
ISBN (Electronic)	9781728162515
DOIs	https://doi.org/10.1109/BigData50022.2020.9377813
State	Published - Dec 10 2020
Event	8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States Duration: Dec 10 2020 → Dec 13 2020

Publication series

Name	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference	8th IEEE International Conference on Big Data, Big Data 2020
Country/Territory	United States
City	Virtual, Atlanta
Period	12/10/20 → 12/13/20

Keywords

Big Data
Data Science
Process Methodology

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/BigData50022.2020.9377813

Cite this

Saltz, J. S., & Hotz, N. (2020). Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. In X. Wu, C. Jermaine, L. Xiong, X. T. Hu, O. Kotevska, S. Lu, W. Xu, S. Aluru, C. Zhai, E. Al-Masri, Z. Chen, & J. Saltz (Eds.), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020 (pp. 2038-2042). Article 9377813 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData50022.2020.9377813

Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. / Saltz, Jeffrey S.; Hotz, Nicholas.
Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. ed. / Xintao Wu; Chris Jermaine; Li Xiong; Xiaohua Tony Hu; Olivera Kotevska; Siyuan Lu; Weijia Xu; Srinivas Aluru; Chengxiang Zhai; Eyhab Al-Masri; Zhiyuan Chen; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. p. 2038-2042 9377813 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

Research output: Chapter in Book/Entry/Poem › Conference contribution

Saltz, JS & Hotz, N 2020, Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. in X Wu, C Jermaine, L Xiong, XT Hu, O Kotevska, S Lu, W Xu, S Aluru, C Zhai, E Al-Masri, Z Chen & J Saltz (eds), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020., 9377813, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, Institute of Electrical and Electronics Engineers Inc., pp. 2038-2042, 8th IEEE International Conference on Big Data, Big Data 2020, Virtual, Atlanta, United States, 12/10/20. https://doi.org/10.1109/BigData50022.2020.9377813

Saltz JS, Hotz N. Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. In Wu X, Jermaine C, Xiong L, Hu XT, Kotevska O, Lu S, Xu W, Aluru S, Zhai C, Al-Masri E, Chen Z, Saltz J, editors, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 2038-2042. 9377813. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). doi: 10.1109/BigData50022.2020.9377813

Saltz, Jeffrey S. ; Hotz, Nicholas. / Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. editor / Xintao Wu ; Chris Jermaine ; Li Xiong ; Xiaohua Tony Hu ; Olivera Kotevska ; Siyuan Lu ; Weijia Xu ; Srinivas Aluru ; Chengxiang Zhai ; Eyhab Al-Masri ; Zhiyuan Chen ; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 2038-2042 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

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Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects

Abstract

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Keywords

ASJC Scopus subject areas

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