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What Drives Success in Data Science Projects: A Taxonomy of Antecedents

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Computational Intelligence, Data Analytics and Applications (ICCIDA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 643))

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Abstract

Organizations have been trying to reshape their business processes and transform them into a smart environment to attain sustainable competitive advantage in their markets. Data science enables organizations to define interconnected and self-controlled business processes by analyzing the massive amount of unstandardized and unstructured high-speed data produced by heterogeneous Internet of Things devices. However, according to the latest research, the success rate of data science projects is lower than other software projects, and the literature review conducted reveals a fundamental need for determining success drivers for data science projects. To address these research gaps, this study investigates the determinants of success and the taxonomy of antecedents of success in data science projects. We reviewed the literature systematically and conducted an expert panel by following a Delphi method to explore the main success drivers of data science projects. The main contributions of the study are twofold: (1) establishing a common base for determinants of success in data science projects (2) guiding organizations to increase the success of their data science projects.

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Authors and Affiliations

  1. Graduate School of Informatics, Middle East Technical University, Ankara, Turkey

    Gonca Tokdemir Gökay, Kerem Nazlıel, Umut Şener & P. Erhan Eren

  2. Department of Computer Engineering, Hacettepe University, Ankara, Turkey

    Ebru Gökalp

  3. Data Analytics Center, Tupras, İstanbul, Turkey

    Mert Onuralp Gökalp, Nergiz Gençal & Gizemnur Dağdaş

Authors
  1. Gonca Tokdemir Gökay
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  2. Kerem Nazlıel
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  3. Umut Şener
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  4. Ebru Gökalp
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  5. Mert Onuralp Gökalp
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  6. Nergiz Gençal
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  7. Gizemnur Dağdaş
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  8. P. Erhan Eren
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Correspondence to Gonca Tokdemir Gökay .

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Editors and Affiliations

  1. University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. National University of Computer and Emerging Sciences, Islamabad, Pakistan

    Akhtar Jamil

  3. Information Systems Engineering, Kocaeli University, Kocaeli, Türkiye

    Süleyman Eken

  4. Department of Computer Engineering, Istinye University, Istanbul, Türkiye

    Alaa Ali Hameed

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Gökay, G.T. et al. (2023). What Drives Success in Data Science Projects: A Taxonomy of Antecedents. In: García Márquez, F.P., Jamil, A., Eken, S., Hameed, A.A. (eds) Computational Intelligence, Data Analytics and Applications. ICCIDA 2022. Lecture Notes in Networks and Systems, vol 643. Springer, Cham. https://doi.org/10.1007/978-3-031-27099-4_35

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