Abstract
Currently, data analysis in higher education institutions is not a luxury, it is a necessity. The large amounts of data generated through university academic functions are the main reason for an analysis and representation of these; since they will allow an adequate decision making in the university academic processes. In this work we propose to perform an analysis of the data generated in the Israel Technological University from Ecuador in the period 2012–2018; for this we apply Data mining algorithms to make suitable predictions and by using data visualization techniques to represent this information allowing us to easily understand it; as a result, relevant information is obtained that will allow the personnel in charge to make the appropriate decisions and improve the processes that have low percentages.
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Provost, F., Fawcett, T.: Data science and its relationship to big data and data-driven decision making. Big Data 1(1), 51–59 (2013)
Xyntarakis, M., Antoniou, C.: Data science and data visualization. In: Mobility Patterns, Big Data and Transport Analytics, pp. 107–144. Elsevier (2019)
Toasa, R., Maximiano, M., Reis, C., Guevara, D.: Data visualization techniques for real-time information—a custom and dynamic dashboard for analyzing surveys’ results. In: 2018 13th Iberian Conference on Information Systems and Technologies, pp. 1–7, June 2018
Rivero, J.L.A., López, J.G.: El proceso de planificación estratégica en las universidades: desencuentros y retos para el mejoramiento de su calidad. Rev. Gestão Univ. na América Lat. - GUAL, vol. 5, no. 2, pp. 72–97, August 2012
Khan, K.S., Kunz, R., Kleijnen, J., Antes, G.: Five steps to conducting a systematic review. J. R. Soc. Med. 96, 118–121 (2003)
Keim, D.A.: Information visualization and visual data mining. IEEE Trans. Vis. Comput. Graph. 7(1), 1–8 (2002)
Waller, M.A., Fawcett, S.E.: Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logist. 34(2), 77–84 (2013)
Román, A.B., Sánchez-Guzmán, D., Salcedo, R.G.: Minería de datos educativa: Una herramienta para la investigación de patrones de aprendizaje sobre un contexto educativo (2014)
West, D.M.: Big data for education: data mining, data analytics, and web dashboards (2012)
Shea, K.D., Brewer, B.B., Carrington, J.M., Davis, M., Gephart, S., Rosenfeld, A.: A model to evaluate data science in nursing doctoral curricula. Nurs. Outlook 67(1), 39–48 (2019)
Steele, J., Iliinsky, N.P.N.: Beautiful visualization : [looking at data through the eyes of experts] (2010)
Kotu, V., Deshpande, B., Kotu, V., Deshpande, B.: Data science process. In: Data Science, pp. 19–37. Morgan Kaufmann (2019)
SistemaEduca: Fases Data Mining. https://sistemeduca.com/fases-data-mining/. Accessed 28 Mar 2019
Keim, D.A.: Visual exploration of large data sets. Commun. ACM 44(8), 38–44 (2001)
SAS: Data Visualization Techniques, White Paper, pp. 2–16 (2013)
Rose, S.: Return on information : the new ROI getting value from data. SAS Inst. Inc., USA (2014)
Sankey Flow Show - Attractive flow diagrams made in minutes! http://www.sankeyflowshow.com/. Accessed 28 Sept 2017
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Baldeon Egas, P.F., Gaibor Saltos, M.A., Toasa, R. (2020). Application of Data Mining and Data Visualization in Strategic Management Data at Israel Technological University of Ecuador. In: Botto-Tobar, M., León-Acurio, J., Díaz Cadena, A., Montiel Díaz, P. (eds) Advances in Emerging Trends and Technologies. ICAETT 2019. Advances in Intelligent Systems and Computing, vol 1066. Springer, Cham. https://doi.org/10.1007/978-3-030-32022-5_39
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DOI: https://doi.org/10.1007/978-3-030-32022-5_39
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