Abstract
The need to maintain better control in the processes of a company, not only commercial but also productive makes it necessary to maintain a focus on the implementation of business tools such as Business Intelligence, which allows to have accurate and statistical data of production in real time and propose solution strategies based on this data. The purpose of this research was to design a Business Intelligence model to facilitate decision making in the production area of an SME in the manufacturing sector. The research has a mixed methodological approach, applied, transversal, prospective and non-experimental, in which the production processes were chosen as a sample and the production area as the unit of study. An interview validated by experts was conducted, along with a documentary analysis based on company records. The Kimball methodology was used to guide the development of the project, which included the creation of a Datamart from the transactional database, the ETL process to load data into the dimensional database and the construction of an OLAP cube for the visualization of reports using Power BI (Business Intelligence).
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CITATION STYLE
Avendaño Delgado, E. M., Santillan, P. J. G., Utrilla, E. J. P., Florián Castillo, O. R., & Deza Castillo, J. M. (2023). Business Intelligence for Decision Making in the Manufacturing Sector. In Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology. Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LEIRD2023.1.1.553
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