Data Pipeline Architecture for the Integration of Technology and Artificial Intelligence in the Competencies of the Future Manager
DOI:
https://doi.org/10.61467/2007.1558.2027.v18i1.1509Keywords:
Technological Competencies, Curriculum Design, Digital Management, Business Intelligence, Competencias tecnológicas, diseño curricular, gestión digital, inteligencia de negociosAbstract
This study addresses the need to update professional profiles in higher education in response to the emergence of Artificial Intelligence (AI) and data science. The objective of this research was to implement a computational data pipeline based on an Extract, Transform, and Load (ETL) approach to automatically assess the technological competencies demanded by the labor market. Using this algorithmic workflow implemented in Python, data collected from a probabilistic sample of 52 companies, determined through the finite population sampling formula with a 5% margin of error, were processed. The results showed that 88.4% of employers prioritized Business Intelligence and Advanced Analytics, while 84.6% emphasized competencies related to Artificial Intelligence-driven process automation. Furthermore, the analysis of the historical enrollment records of 3,149 students confirmed the institutional operational feasibility and provided the technical evidence that supported the official approval of the proposed Digital Management and Business Intelligence specialization at the Technological Institute of Pachuca. The findings demonstrate that the proposed ETL-based architecture provides an effective data-driven framework for curriculum decision-making in higher education.
Spanish-language metadata / Metadatos en español
Título en español:
Arquitectura de un pipeline de datos para la integración de la tecnología y la inteligencia artificial en las competencias del futuro directivo
Resumen:
Este estudio aborda la necesidad de actualizar los perfiles profesionales en la educación superior ante la aparición de la Inteligencia Artificial (IA) y la ciencia de datos. El objetivo de esta investigación fue implementar un pipeline computacional de datos basado en un enfoque de extracción, transformación y carga (ETL) para evaluar automáticamente las competencias tecnológicas demandadas por el mercado laboral.
Mediante este flujo de trabajo algorítmico implementado en Python, se procesaron los datos recopilados de una muestra probabilística de 52 empresas, determinada mediante la fórmula de muestreo para poblaciones finitas con un margen de error del 5 %. Los resultados mostraron que el 88,4 % de los empleadores priorizó la Inteligencia de Negocios y la Analítica Avanzada, mientras que el 84,6 % destacó las competencias relacionadas con la automatización de procesos mediante Inteligencia Artificial.
Asimismo, el análisis de los registros históricos de matrícula de 3.149 estudiantes confirmó la viabilidad operativa institucional y proporcionó la evidencia técnica que sustentó la aprobación oficial de la especialidad propuesta en Gestión Digital e Inteligencia de Negocios en el Instituto Tecnológico de Pachuca. Los hallazgos demuestran que la arquitectura propuesta basada en ETL proporciona un marco eficaz y basado en datos para la toma de decisiones curriculares en la educación superior.
Palabras Claves:
Competencias tecnológicas, diseño curricular, gestión digital, inteligencia de negocios.
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