Bibliographic citations
Machado, J., Matos, C. (2024). Dashboard en Business intelligence para optimizar el seguimiento del uso de automóviles en un concesionario automotriz [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/674240
Machado, J., Matos, C. Dashboard en Business intelligence para optimizar el seguimiento del uso de automóviles en un concesionario automotriz [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/674240
@misc{renati/418733,
title = "Dashboard en Business intelligence para optimizar el seguimiento del uso de automóviles en un concesionario automotriz",
author = "Matos Gavino, Carlos Danny",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
In this paper, a problem was identified in a car dealership, the existence of limited control in the provision of maintenance services that has reached the point of presenting a 15% reduction in sales, since the after-sales area does not I had a control to estimate the next maintenance visits of the clients. Finally, the implementation of a business intelligence dashboard is proposed to optimize the monitoring of car usage in an automotive dealership in order to solve the problem. To achieve the development of the business intelligence dashboard, four objectives were proposed to achieve it. The first objective allows us to analyze the data and BI platforms that were chosen for the implementation. The second objective allows us to design a mockup that allows us to see what the board would look like and what elements were necessary to automate the after-sales monitoring process. The third objective allowed us to validate the implementation through a testing scenario using measurement metrics, in this case the accuracy of the data. The last objective helped us create a continuity plan that ensures that the implementation continues in the future. Likewise, from the validation of the implementation we can confirm that it was possible to increase maintenance services by 14% and that the proposal presents accuracy in the data to obtain exact dates of the clients' next maintenance.
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