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La inteligencia de negocio como apoyo a la toma de decisiones en el ámbito académico (Business Intelligence as decision support system in academic environment)

Author

Listed:
  • Yusnier Reyes Dixson

    (Universidad de las Ciencias Informáticas)

  • Lissette Nuñez Maturel

    (Centro Nacional de Genética Médica)

Abstract

Spanish abstract Las organizaciones competitivas han establecido sistemas de inteligencia de negocio para proporcionar a sus trabajadores herramientas que les ayuden en la toma de decisiones (Guitart y Conesa, 2014). El acertado flujo y gestión de datos e información es vital para un acertado proceso de toma de decisiones. Esta táctica trasladada al ámbito universitario significa proporcionar a profesores y directivos sistemas que apoyen la toma de decisiones en su actividad docente (Guitart y Conesa, 2014). A pesar de las ventajas que ha propiciado el uso de estos sistemas y de las dificultades detectadas con el tratamiento y la forma en que se utilizan los datos para dar soporte a las decisiones en el ámbito académico universitario, no se ha evidenciado un uso sistemático de los mismos. Debido al aumento del volumen de los datos almacenados, los profesores y directivos se enfrentan a un ambiente de incertidumbre y complejidad crecientes. Generalmente no se cuenta con las herramientas necesarias para manipular estos datos y convertirlos en información valiosa. Este trabajo tuvo como objetivo desarrollar un sistema basado en inteligencia de negocios que permita capturar, almacenar, procesar, analizar y mostrar de manera eficiente, los datos generados en el proceso de formación. La propuesta fue utilizada con datos reales del primer año de una facultad de la Universidad de las Ciencias Informáticas en los cursos 2012-2013, 2013-2014 y del primer semestre del curso 2014-2015 a partir de lo cual se obtuvo información útil para la toma de decisiones. Por último se propuso un conjunto de elementos organizativos para la correcta utilización del sistema. English abstract Competitive organizations have established business intelligence systems to provide their workers with tools to help them in decision-making (Guitart and Conesa, 2014). The successful flow and management of data and information is vital for a successful decision-making process. This tactic transferred to the university level means providing systems to teachers and managers in order to support decision making in their teaching activity (Guitart and Conesa, 2014). Despite the advantages that has led to the use of these systems and the difficulties encountered with treatment and how the data are used to support decisions on the academic level, it has not seen a systematic use of the same. Due to the increased volume of stored data, teachers and administrators face an environment of uncertainty and increasing complexity. Generally it not has the necessary tools to manipulate these data and turn it into valuable information. This study aimed to develop a business based on intelligence that enables capture, store, process, analyze and display efficiently, the data generated in the educational process. The proposal was used with data from the first year of a faculty of the University of Information Science in 2012-2013, 2013-2014 and first semester of courses in 2014 and 2015 from which useful information was obtained for decision making. Finally a set of organizational elements for the proper use of the system was proposed.

Suggested Citation

  • Yusnier Reyes Dixson & Lissette Nuñez Maturel, 2015. "La inteligencia de negocio como apoyo a la toma de decisiones en el ámbito académico (Business Intelligence as decision support system in academic environment)," Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), vol. 3(2), pages 67-73.
  • Handle: RePEc:rge:journl:v:3:y:2015:i:2:p:67-73
    DOI: 10.5281/zenodo.7080890
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    Keywords

    Datos académicos; Toma de decisiones; Inteligencia de negocio; Business Intelligence; Decision making; Academic data;
    All these keywords.

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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