Aplicativo de inteligencia de negocios para la toma de decisiones en la gerencia de administración tributaria de la Municipalidad Provincial de Loreto Nauta 2023

• Autor: Pizango Tapullima, Roque Fernando
• Formato: tesis de maestría
• Fecha de Publicación: 2024
• Institución: Universidad Nacional De La Amazonía Peruana
• Repositorio: UNAPIquitos-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.unapiquitos.edu.pe:20.500.12737/10553
• Enlace del recurso: https://hdl.handle.net/20.500.12737/10553
• Nivel de acceso: acceso abierto
• Materia: Sistemas de información para la gestión; Inteligencia económica; Toma de decisiones; Municipalidad; https://purl.org/pe-repo/ocde/ford#2.02.04

This thesis was developed within the Tax Administration Management of the Provincial Municipality of Loreto – Nauta in the year 2023, which presented integration problems in the decision-making processes and which until then did not have an application that is friendly and understanding to obtain a situational diagnosis that helps predict better tax collection. Reason why the following research question was intended to be resolved: How to improve decision making in the GAT of the MPL – N through the use of a Business Intelligence Application? Whose general objective was: Optimize decision making in the Tax Administration Management of the Provincial Municipality of Loreto - Nauta, through the use of a Business Intelligence Application. Being an applied type research and at a descriptive and applicative level with a quasi experimental experimental design with post-test and control group, it is also necessary to indicate that the BI Application was built based on Ralph Kimball's methodology, the same as It guides us better for these types of applications. After the study, the following results were obtained: with the BI Application, a reduction in time of at least 25.75 seconds was achieved in obtaining tax collection reports, a reduction in time of at least 113.64 seconds was achieved in Obtaining reports on management indicators, a reduction in decision-making time of at least 7.98 minutes was achieved; where, finally, it is concluded with the acceptance of the three specific hypotheses raised by the researcher, which seek optimization in decision making with the use of the BI Application.