État académique
Thèse en cours...
Sujet: De la Business Intelligence interne à la BI sur le nuage : modèles et apports méthodologiques
Direction de thèse:
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
Design Science Research Contribution to Business Intelligence in the Cloud – A Systematic Literature Review
International audience
Business intelligence (BI) helps managers make informed decisions. In the age of big data, BI technology provides essential support for decision making. Cloud computing also attracts many organizations because of its potential: ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services). This paper focuses on the deployment of BI in the cloud, from the vantage point of design science research (DSR). We produce a state of the art of research pertaining to BI in the cloud, following the methodology of systematic literature review. This literature review especially exhibits the different artifacts proposed by design science researchers regarding BI in the cloud. To structure the literature review, we propose a framework composed of two dimensions: artifact type and BI step. In particular, we propose a typology of artifact types, refining the coarse-grained typology commonly used in DSR. We use the two-dimensional framework both to map the current state of DSR regarding BI in the cloud, and to elicit future research avenues in terms of design science artifacts for BI in the cloud. The contribution is threefold: the literature review may help DSR researchers get an overview of this active research domain; the two-dimensional framework facilitates the understanding of different research streams; finally, the proposed future topics may guide researchers in identifying promising research avenues.
ISSN: 0167-739X Future Generation Computer Systems https://hal.archives-ouvertes.fr/hal-01639025 Future Generation Computer Systems, Elsevier, 2016ARRAY(0x7fe6a72e9e10) 2016
Business Intelligence and Big Data in the Cloud: Opportunities for Design-Science Researchers
Advances in Conceptual Modeling - Proceedings of ER 2014 Workshops https://hal.archives-ouvertes.fr/hal-01126547 Advances in Conceptual Modeling - Proceedings of ER 2014 Workshops, Oct 2014, Atlanta, GA, United States. Springer, LNCS 8823, pp.75-84, 2014ARRAY(0x7fe6a6f85418) 2014-10-27