METODOLOGÍA PARA PROCESOS DE INTELIGENCIA DE NEGOCIOS CON MEJORAS EN LA EXTRACCIÓN Y TRANSFORMACIÓN DE FUENTES DE DATOS

Abstract

The fact of not having a clear method to be efficient in the search of decisions in business intelligence (IN) generate high costs in the use of resources, reason why, the computer science got to solve this problem through a branch of the same that is the artificial intelligence and in a subfield as is the Automatic Learning (AA). In the present work, a methodology called M3S of IN is defined, in which, an adequate procedure is determined to be followed to have the best results in the extraction of information, to obtain greater knowledge and value in the information; in turn, the methodology is based on the decision tree algorithm ID3, which is based on mathematical concepts such as entropy and information gain within the analysis of the best attributes that can be considered for decision making.