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A State-of-the-Art Overview and Future Research Avenues of Self-Service Business Intelligence and Analytics

Michalczyk, Sven; Nadj, Mario; Azarfar, Darius; Mädche, Alexander; Gröger, Christoph

Abstract:
Self-Service Business Intelligence and Analytics (SSBIA) is an upcoming approach and trend that enables casual business users to prepare and analyze data with easy-to-use Business Intelligence and Analytics (BIA) systems without being reliant on expert support or power users to perform their (complex) analytical tasks easier and faster than before. Despite a strong interest of scholars and practitioners in SSBIA, the understanding about its underlying characteristics is limited. Furthermore, there is a lack of a structured and systematic form in which SSBIA research can be classified. Against this backdrop, this article showcases the current state-of-the-art of SSBIA research along four key areas in the field: (1) perspectives on SSBIA, (2) user roles involved, (3) required expertise, and (4) supported levels of self-service. Analyzing 60 articles, our main contribution resides in the synopsis of SSBIA literature in these four areas. For instance, we illustrate that there exist three perspectives of SSBIA: artefact-centric (45% of analyzed studies), user-centric (82%), and governance-centric (25%). On the basis of our analysis, we suggest promising avenues, which will support scholars in their endeavors on how to pursue with future avenues in the field of SSBIA (for e.g., understanding the trade-off between top-down and bottom-up capabilities).



Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2020
Sprache Englisch
Identifikator KITopen-ID: 1000119927
Erschienen in ECIS 2020 Proceedings - Twenty-Eighth European Conference on Information Systems, Marrakesh, Marokko, June 15 - 17, 2020
Veranstaltung 28th European Conference on Information Systems (ECIS 2020), Marrakesch, Marokko, 15.06.2020 – 17.06.2020
Bemerkung zur Veröffentlichung Die Veranstaltung fand wegen der Corona-Pandemie als Online-Event statt
Schlagwörter Self-Service, Business Intelligence, Analytics, Literature Review
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