Framework para la administración de activos tecnológicos basado en Big Data
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Date
2025
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Institución Universitaria Pascual Bravo
Abstract
En la era digital, el manejo eficiente de los activos tecnológicos es fundamental para garantizar la competitividad y sostenibilidad de las empresas. La aplicación de Big Data ha revolucionado la administración de estos activos, permitiendo una gestión basada en datos que optimiza el rendimiento y prolonga su ciclo de vida. En este trabajo presenta un Framework para la implementación de Big Data en la administración de activos tecnológicos en una empresa prestadora de servicios de instalaciones eléctricas. A través del análisis de grandes volúmenes de información, las empresas pueden tomar decisiones estratégicas soportadas en información, reduciendo costos operativos, mejorando la planificación de mantenimiento y anticipando posibles fallos antes de que ocurran. El Framework cuenta con visualizaciones del inventario de activos, ciclos de vida, gestión de asignaciones de recursos tecnológicos, gestión financiera, análisis de riesgos, depreciación y predicción de costos, impactando en la eficiencia operativa, la reducción de tiempos de inactividad y el incremento de la productividad en organizaciones del sector. El Framework propuesto con la integración de Big Data no solo mejora la administración de activos, sino que también aporta valor estratégico a la empresa, facilitando la toma de decisiones y fortaleciendo su posición en el mercado.
Abstract In the digital era, the efficient management of technological assets is essential to ensure the competitiveness and sustainability of companies. The application of big data has revolutionized asset management by enabling data-driven strategies that optimize performance and extend asset lifecycles. This paper presents a framework for implementing big data in the management of technological assets within a company that provides electrical installation services. Through the analysis of large volumes of information, companies can make strategic, data-supported decisions, reducing operational costs, improving maintenance planning, and anticipating potential failures before they occur. The framework includes visualizations of asset inventory, lifecycle tracking, technological resource allocation management, financial management, risk analysis, depreciation, and cost prediction. These elements contribute to operational efficiency, reduced downtime, and increased productivity in organizations within the sector. The proposed framework, with the integration of big data, not only enhances asset management but also delivers strategic value to the company by facilitating decisionmaking and strengthening its market position.
Abstract In the digital era, the efficient management of technological assets is essential to ensure the competitiveness and sustainability of companies. The application of big data has revolutionized asset management by enabling data-driven strategies that optimize performance and extend asset lifecycles. This paper presents a framework for implementing big data in the management of technological assets within a company that provides electrical installation services. Through the analysis of large volumes of information, companies can make strategic, data-supported decisions, reducing operational costs, improving maintenance planning, and anticipating potential failures before they occur. The framework includes visualizations of asset inventory, lifecycle tracking, technological resource allocation management, financial management, risk analysis, depreciation, and cost prediction. These elements contribute to operational efficiency, reduced downtime, and increased productivity in organizations within the sector. The proposed framework, with the integration of big data, not only enhances asset management but also delivers strategic value to the company by facilitating decisionmaking and strengthening its market position.
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Keywords
Big Data, Gestión financiera, Productividad, Toma de decisiones, Framework, Administración de activos, Inventario de activos, Análisis de riesgos