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Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation

Author

Listed:
  • Jens Passlick

    (Leibniz Universität Hannover)

  • Lukas Grützner

    (Leibniz Universität Hannover)

  • Michael Schulz

    (Nordakademie)

  • Michael H. Breitner

    (Leibniz Universität Hannover)

Abstract

Self-service business intelligence and analytics (SSBIA) empowers non-IT users to create reports and analyses independently. SSBIA methods and processes are discussed in the context of an increasing number of application scenarios. However, previous research on SSBIA has made distinctions among these scenarios only to a limited extent. These scenarios include a wide variety of activities ranging from simple data retrieval to the application of complex algorithms and methods of analysis. The question of which dimensions are suitable for differentiating SSBIA application scenarios remains unanswered. In this article, we develop a taxonomy to distinguish among SSBIA applications more effectively by analyzing the relevant scientific literature and current SSBIA tools as well as by conducting a case study in a company. Both researchers and practitioners can use this taxonomy to describe and analyze SSBIA scenarios in further detail. In this way, the opportunities and challenges associated with SSBIA application can be identified more clearly. In addition, we conduct a cluster analysis based on the SSBIA tools thus analyzed. We identify three archetypes that describe typical SSBIA tools. These archetypes identify the application scenarios that are addressed most frequently by SSBIA tool providers. We conclude by highlighting the limitations of this research and suggesting an agenda for future research.

Suggested Citation

  • Jens Passlick & Lukas Grützner & Michael Schulz & Michael H. Breitner, 2023. "Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation," Information Systems and e-Business Management, Springer, vol. 21(1), pages 159-191, March.
  • Handle: RePEc:spr:infsem:v:21:y:2023:i:1:d:10.1007_s10257-022-00574-3
    DOI: 10.1007/s10257-022-00574-3
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    References listed on IDEAS

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    1. Paul Alpar & Michael Schulz, 2016. "Self-Service Business Intelligence," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(2), pages 151-155, April.
    2. Jeffrey G. Miller & Aleda V. Roth, 1994. "A Taxonomy of Manufacturing Strategies," Management Science, INFORMS, vol. 40(3), pages 285-304, March.
    3. Alberto Abelló & Jérôme Darmont & Lorena Etcheverry & Matteo Golfarelli & Jose-Norberto Mazón & Felix Naumann & Torben Pedersen & Stefano Bach Rizzi & Juan Trujillo & Panos Vassiliadis & Gottfried Vos, 2013. "Fusion Cubes: Towards Self-Service Business Intelligence," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 9(2), pages 66-88, April.
    4. David Schuff & Karen Corral & Robert D. St. Louis & Greg Schymik, 2018. "Enabling self-service BI: A methodology and a case study for a model management warehouse," Information Systems Frontiers, Springer, vol. 20(2), pages 275-288, April.
    5. Dejan Zilli, 2014. "Self-Service Business Intelligence for Higher Education Management," Human Capital without Borders: Knowledge and Learning for Quality of Life; Proceedings of the Management, Knowledge and Learning International Conference 2014,, ToKnowPress.
    6. Yan Li & Manoj A. Thomas & Kweku-Muata Osei-Bryson, 2017. "Ontology-based data mining model management for self-service knowledge discovery," Information Systems Frontiers, Springer, vol. 19(4), pages 925-943, August.
    7. Mayer, J. H. & Röder, A. & Hartwig, J. & Quick, Reiner, 2014. "A Self-Service MSS Design from a New-Generation Manager Perspective," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 67557, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Henner Gimpel & Daniel Rau & Maximilian Röglinger, 2018. "Understanding FinTech start-ups – a taxonomy of consumer-oriented service offerings," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 245-264, August.
    9. Schulz, Michael & Winter, Patrick & Choi, Sang-Kyu Thomas, 2015. "On the relevance of reports—Integrating an automated archiving component into a business intelligence system," International Journal of Information Management, Elsevier, vol. 35(6), pages 662-671.
    10. Robert C Nickerson & Upkar Varshney & Jan Muntermann, 2013. "A method for taxonomy development and its application in information systems," European Journal of Information Systems, Taylor & Francis Journals, vol. 22(3), pages 336-359, May.
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