Managing and Composing Teams in Data Science: An Empirical Study

Timo Aho, Terhi Kilamo, Lucy Lwakatare, Tommi Mikkonen, Outi Sievi-Korte, Sezin Yaman

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

Data science projects have become commonplace over the last decade. During this time, the practices of running such projects, together with the tools used to run them, have evolved considerably. Furthermore, there are various studies on data science workflows and data science project teams. However, studies looking into both workflows and teams are still scarce and comprehensive works to build a holistic view do not exist. This study bases on a prior case study on roles and processes in data science. The goal here is to create a deeper understanding of data science projects and development processes. We conducted a survey targeted at experts working in the field of data science (n=50) to understand data science projects’ team structure, roles in the teams, utilized project management practices and the challenges in data science work. Results show little difference between big data projects and other data science. The found differences, however, give pointers for future research on how agile data science projects are, and how important is the role of supporting project management personnel. The current study is work in progress and attempts to spark discussion and new research directions.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Big Data (Big Data)
PublisherIEEE
Pages2291-2300
Number of pages10
ISBN (Electronic)978-1-6654-3902-2
DOIs
Publication statusPublished - 2021
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Big Data - , United States
Duration: 15 Dec 202118 Dec 2021

Conference

ConferenceIEEE International Conference on Big Data
Country/TerritoryUnited States
Period15/12/2118/12/21

Keywords

  • Conferences
  • Project management
  • Data science
  • Big Data
  • Data models
  • Sparks
  • Personnel
  • agile practices
  • teamwork
  • project management

Publication forum classification

  • Publication forum level 1

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