Business intelligence solution for managing educational resources and physical spaces in Magdalena University
Keywords:
Business intelligence, Data warehouse, Extreme programming, Resource managementAbstract
This article describes a business intelligence solutionfor managing educational resources andphysical space at the University of Magdalena.With this solution we can get current and historicalreports of processes, making decisionssuch as purchase of new resources, forecastthe occupation or use of resources, improvethe availability of resources, and others. Forthe development of the solution was used theplatform of Microsoft Business IntelligenceSQL Server 2008 R2, the process modeling wasmade using BPMN; for the ETL diagrams anddata warehouse modeling was used UML. Themethod followed was an adaptation of ExtremeProgramming to the Business Intelligence solutionenvironment.
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References
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2. Power. (10 de marzo de 2007). A brief historyof decision support system, version 4.1. Recuperadoel 28 de Enero de 2013, de DSSResources.com
3. Gartner. (18 de febrero de 2011). Gartner ForecastsGlobal Business Intelligence Market toGrow 9.7 Percent in 2011. Recuperado el 24 deNoviembre de 2012, de http://www.gartner.com/newsroom/id/1553215
4. Tereso, M. (2011). Open source business intelligencetools for SMEs . Information Systemsand Technologies (CISTI), 1 - 4 .
5. Conesa Caralt, J., & Curto Díaz, J. (2010). Introducciónal Business Intelligence. Barcelona:Editorial UOC.
6. Oficina Asesora de Planeación. (2010). BoletínEstadístico 2010. Magdalena. Santa Marta,D.T.C.H.: Universidad del Magdalena.
7. Universidad del Magdalena. (2012). Resolución143. Santa Marta.
8. Dresner, H. (2009). Profiles in Performance:Business Intelligence Journeys and the Roadmapfor Change. Wiley.
9. Vodapalli, N. K. (2009). Critical Success Factorsof BI Implementation. Copenhague: ITUniversity of Copenhagen.
10. Azma, F. (2011). Business intelligence as a keystrategy for development organizations. FirstWorld Conference on Innovation and ComputerSciences (INSODE 2011).
11. Kimball, R. (2008). Data Warehouse the lifecycle.
12. Beck, K. (2004). Extreme Programming Explained:Embrace Change, 2nd Edition. Addison-Wesley.
13. Ramos, S. (2011). Microsoft Business Intelligence:vea el cubo medio lleno. Albatera: SolidQPress.
14. Lujan, S., & Trujillo, J. (2002). Extending UMLfor Multidimensional Modeling. Lecture Notesin Computer Science, 290-304.
15. Gartner. (2012). Magic Quadrant For BusinessIntelligence Platforms.
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Published
2013-06-01
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Articles
How to Cite
Business intelligence solution for managing educational resources and physical spaces in Magdalena University. (2013). Avances: Investigación En Ingeniería, 10(1), 09-19. https://revistas.unilibre.edu.co/index.php/avances/article/view/2721
