Software de predicción de ventas en una PYME basado en técnicas de aprendizaje automático

Abstract

The following research project aims to implement a software to predict the sales of an SME with the help of machine learning techniques, as this is a fundamental tool for automatic learning which can help the efficient management of the company around the information obtained, to realize these integrations will be designed and implemented software architectures based on microservices. The methodology used is qualitative, because observation was used as an evaluation tool and the type of research was descriptive, since all the realization of the software was detailed, where we had as results that the exploration of the different approaches, allowed Mongo Atlas to make the right decision to develop this work, since the process required to investigate the needs and understand the business, which other technologies could not provide. Although methods such as SEMMA can simplify the process, the standardization of steps provided by the method used promotes an organized and efficient development. Concluding that the model that was performed allowed the input of data for the automation of sales predictions, evaluating the performance of the software in determining sales, and thus, implement a Software to predict the sales of an SME with the help of machine learning techniques.