Data Mining in the Contractual Management of the Brazilian Ministry of Health: A Case Study

Abstract

Data mining is a process of analyzing data from different perspectives and summarizing it into useful information that can be used to classify data samples. Basically data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Machine learning is a branch of artificial intelligence which works with construction and study of systems that can learn from data. The core of machine learning deals with representation and generalization. The use of Data Mining is an important activity to control the development process of a software factory. Outsourcing software development by public and private organizations requires continuous monitoring to ensure compliance with service levels and small inspection teams coexist with work overload. This study seeks to apply data mining techniques and machine learning algorithms to create models to predict the delay in the delivery of demands. Following the CRISP-DM reference model, this study presents the process of creation and application of a predictive model for the contractual management of the Brazilian Ministry of Health.