Toward big data and analytics governance: redefining structural governance mechanisms

Détails

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Etat: Public
Version: Final published version
Licence: CC BY-NC-ND 4.0
ID Serval
serval:BIB_28031AFE9A70
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Toward big data and analytics governance: redefining structural governance mechanisms
Titre de la conférence
54th Hawaii International Conference on System Sciences 2021
Auteur⸱e⸱s
Fadler Martin, Legner Christine
Editeur
University of Hawai'i at Manoa
Statut éditorial
Publié
Date de publication
05/01/2021
Peer-reviewed
Oui
Langue
anglais
Résumé
Big Data and Analytics (BDA) enable innovative business models and, simultaneously, increase existing business processes’ efficiency and effectiveness. Although BDA’s potential is widely recognized, companies face a variety of challenges when adopting BDA and endeavoring to generate business value. Researchers and practitioners emphasize the need for effective governance to delineate data and analytics’ roles and responsibilities. Existing studies focus either on data or on analytics governance, even though both approaches are closely interlinked and depend on each other. Our study aims to integrate these two distinct research perspectives into a unified view on structural mechanisms for BDA. Using design science research, we iteratively develop data and analytics roles, clarify their responsibilities and provide guidelines for their organizational assignment. Our study contributes to advancing research on data and analytics governance and supports practitioners managing BDA.
Mots-clé
Business Intelligence, Business Analytics and Big Data, Analytics Governance, Data Governance, Roles and Responsibilities, Structural Governance Mechanisms
Open Access
Oui
Financement(s)
Autre / Competence Center Corporate Data Quality (CC CDQ)
Création de la notice
02/01/2021 12:29
Dernière modification de la notice
03/01/2021 7:08
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