El uso de herramientas case de BI para la toma de decisiones estratégicas en las instituciones de educación superior de Sinaloa
DOI:
https://doi.org/10.61273/neyart.v4i3.174Keywords:
BI, Business Intelligence, CASE tools, decision-making, higher education, Sinaloa, TecNMAbstract
This article analyzes the use of CASE tools applied to Business Intelligence (BI) as support for strategic decision-making in higher education institutions in the state of Sinaloa, taking the National Technological Institute of Mexico (TecNM) as a case study. Through a comparative and recommendation-based approach, various CASE tools oriented toward BI process management are examined, including Power BI, Pentaho, Talend, and Oracle Data Integrator, with the aim of determining their relevance and efficiency in academic environments. The research was conducted under a quantitative-descriptive approach, using information from TecNM’s statistical records between 2019 and 2025. A methodological model based on the stages of the BI process (extraction, transformation, loading, modeling, and visualization) was implemented to evaluate the performance of the tools in each phase. The results show that Power BI and Pentaho offer greater adaptability for public educational institutions due to their ease of implementation, technical support, and compatibility with different data sources. Likewise, opportunities were identified in the automation of the ETL flow through Talend and in scalability with Oracle Data Integrator. The study concludes that the integration of CASE tools into institutional BI systems contributes to the consolidation of a culture of evidence-based decision-making, improving administrative efficiency, transparency, and the analytical capacity of higher education institutions.
Downloads
Metrics
References
Arias, F., & Torres, L. (2021). Aplicación de sistemas de inteligencia de negocios en universidades públicas latinoamericanas: Retos y oportunidades. Revista Iberoamericana de Tecnología Educativa, 17(2), 45–60. https://doi.org/10.21556/edutec.2021.17.2.45
Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. En J. A. Larusson & B. White (Eds.), Learning analytics: From research to practice (pp. 61–75). Springer. https://doi.org/10.1007/978-1-4614-3305-7_4
Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230
Eckerson, W. W. (2011). Performance dashboards: Measuring, monitoring, and managing your business (2nd ed.). John Wiley & Sons.
Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5–6), 304–317. https://doi.org/10.1504/IJTEL.2012.051816
Few, S. (2013). Information dashboard design: Displaying data for at-a-glance monitoring (2nd ed.). Analytics Press.
García-Peñalvo, F. J., & Conde, M. Á. (2019). Big data y analítica educativa: una revisión sistemática de la literatura. RIED: Revista Iberoamericana de Educación a Distancia, 22(2), 81–106. https://doi.org/10.5944/ried.22.2.23412
Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling (3rd ed.). John Wiley & Sons.
Picciano, A. G. (2012). The evolution of big data and learning analytics in American higher education. Journal of Asynchronous Learning Networks, 16(3), 9–20. https://doi.org/10.24059/olj.v16i3.267
Power, D. J. (2014). Decision support, analytics, and business intelligence (2nd ed.). Business Expert Press.
Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3), e1355. https://doi.org/10.1002/widm.1355
Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40.
Turban, E., Sharda, R., Delen, D., & King, D. (2020). Business intelligence: A managerial approach (5th ed.). Pearson Education.
Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. Computer, 40(9), 96–99. https://doi.org/10.1109/MC.2007.331
Yigitbasioglu, O. M., & Velcu, O. (2012). A review of dashboards in performance management: Implications for design and research. International Journal of Accounting Information Systems, 13(1), 41–59. https://doi.org/10.1016/j.accinf.2011.08.002.
