Volume 47, Issue 1, February 2020, Pages 29–50
ENGOMBE WEDI Boniface1, Okit’oleko On’okoko Wenga2, and Kafunda Katalay3
1 Université Pédagogique Nationale de Kinshasa, RD Congo
2 Institut Supérieur de Statistique de Kinshasa, RD Congo
3 Université de Kinshasa, RD Congo
Original language: French
Copyright © 2020 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The work carried out consists of a framework for evaluation and support of a project to develop decision support tools based on data warehouse for the management of the forecast of Higher Education Institutions and Universities, EESU/HEIU in acronym. Currently, these tools occupy a prominent position in the evolution perspective of the management of infrastructure capacity according to student enrolment for each academic year by 2090 using the simple linear regression line. In this article, we are working on designing, implementing, and securing a Meta Object – class data warehouse deployed in a high – speed, optical fiber backbone environment. Then, we were interested in realizing EESU/HEIU management software around the nine most popular targeted applications, thanks to the WINDEV development platform.
Author Keywords: approach, design, support tools, decision, data warehouse.
ENGOMBE WEDI Boniface1, Okit’oleko On’okoko Wenga2, and Kafunda Katalay3
1 Université Pédagogique Nationale de Kinshasa, RD Congo
2 Institut Supérieur de Statistique de Kinshasa, RD Congo
3 Université de Kinshasa, RD Congo
Original language: French
Copyright © 2020 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The work carried out consists of a framework for evaluation and support of a project to develop decision support tools based on data warehouse for the management of the forecast of Higher Education Institutions and Universities, EESU/HEIU in acronym. Currently, these tools occupy a prominent position in the evolution perspective of the management of infrastructure capacity according to student enrolment for each academic year by 2090 using the simple linear regression line. In this article, we are working on designing, implementing, and securing a Meta Object – class data warehouse deployed in a high – speed, optical fiber backbone environment. Then, we were interested in realizing EESU/HEIU management software around the nine most popular targeted applications, thanks to the WINDEV development platform.
Author Keywords: approach, design, support tools, decision, data warehouse.
Abstract: (french)
Le travail effectué consiste en un cadre d’évaluation et d’accompagnement d’un projet de développement des outils d’aide à la décision basés sur datawarehouse pour la gestion prévisionnelle des Etablissements d’Enseignement Supérieur et Universitaire, EESU en sigle. Actuellement, ces outils occupent une place prépondérante dans la perspective évolutive de la gestion prévisionnelle de la capacité d’accueil des infrastructures en fonction des effectifs des étudiants pour chaque année académique à l’horizon 2090 par usage de la droite de régression linéaire simple. Dans cet article, nous travaillons sur la conception, l’implémentation et la sécurisation d’un méta entrepôts objet-classe de données déployé dans un environnement backbone à fibre optique connecté sur Internet à haut débit. Ensuite, nous nous sommes intéressés à réaliser un logiciel de gestion des EESU autour des neuf applications les plus répandues ciblées grâce à la plateforme de développement WINDEV.
Author Keywords: approche, conception, outils d’aide, décision, datawarehouse.
How to Cite this Article
ENGOMBE WEDI Boniface, Okit’oleko On’okoko Wenga, and Kafunda Katalay, “UNE APPROCHE DE CONCEPTION DES OUTILS D’AIDE A LA DECISION BASES SUR DATAWAREHOUSE,” International Journal of Innovation and Scientific Research, vol. 47, no. 1, pp. 29–50, February 2020.
