5 janvier 2021
Ce document est lié à :
info:eu-repo/grantAgreement/OTHER//Competence Center Corporate Data Quality (CC CDQ)///
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_28031AFE9A703
info:eu-repo/semantics/openAccess , CC BY-NC-ND 4.0 , https://creativecommons.org/licenses/by-nc-nd/4.0/
Martin Fadler et al., « Toward big data and analytics governance: redefining structural governance mechanisms », Serveur académique Lausannois, ID : 10670/1.o7wask
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.