Critical Success Factors in Data Analytics Projects: Insights from a Systematic Literature Review

Date

2024-09-10

Author

Demir, Nisa
Aysolmaz, Banu
Özcan Top, Özden

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Various data analytics applications are increasingly used by organizations to extract insights from data. There are numerous studies exploring the critical success factors (CSFs) in different data analytics fields including Business Intelligence, Artificial Intelligence, Machine Learning, Data Science, and Big Data. Despite the extensive body of research, there remains a gap in identifying a structured CSFs list that offers a holistic view across all these fields. This study addresses this gap by conducting a systematic literature review to investigate CSFs in data analytics projects, aiming to create a comprehensive list that is applicable across various fields. We have categorized CSFs into six key themes: People, Strategy, Technology & Data, Organizational Culture, Process Design and External Factors derived from 28 research papers. By presenting these CSFs comprehensively, this paper seeks to provide a structured approach that will enhance the success rates of data analytics projects, facilitating better strategic alignment and operational efficiency across multiple fields.

URI

https://link.springer.com/chapter/10.1007/978-3-031-72234-9_11
https://hdl.handle.net/11511/111191

Collections

Graduate School of Informatics, Conference / Seminar