Description
A huge amount of data has been collected and stored by companies year after
year. However, most of them are not being analyzed in order to boost the business.
Data Mining is a tool that is a tool that aims to analyze databases and extract useful
information to generate insights and assist managers in decision making. Related to
this topic, this monograph had as objective to find rules of association between
frequent items, analyzing a database of a supermarket, from the Market Basket
Analysis. For this, a strategy of extraction, treatment and loading of data was
structured, and a computational model was developed to be used in software R for
apriori algorithm application. Following the model, the most frequent item from the
database were found, as well as the association rules and, from the results, four sales
combos were proposed for the supermarket. The study has proven that the tool can
become a great ally to make more assertive decisions for the business. This work can
be used as a basis for further research and, in addition, provides a model that can be
replicated in different segments.
