Made available in DSpace on 2015-04-14T14:49:43Z (GMT). No. of bitstreams: 1 437994.pdf: 1640213 bytes, checksum: 26f32168808fae3383c6bd3a3b9c87fc (MD5) Previous issue date: 2010-03-30 / Organizations acting on several markets have been using the benefits offered by the use of Data Mining - DM techniques as a complementary activity to their support systems to the strategic decision. However, to the great majority of the organizations, the deployment of a DM Project ends up not being feasible due to different factors, such as: Project duration, high costs and mainly by the uncertainty as to getting results that may effectively help the organization to improve their business processes. In this context, this paper presents a process based on the process of knowledge Discovery in Database - KDD which aims to identify opportunities to the application of DM techniques through the induction and ranking of decisions generated by the exploration of semi automatic Online Analytical Processing Models-OLAP. The built process uses stored information in a OLAP model prepared on the basis of used information by Customer Relationship Management - CRM and Business Intelligence - BI typically used by the organization to support strategic decision making. In relation to the information selected for this research, it has been carried out in a semi automatic way, a series of experiments using DM techniques which the results are collected and stored for later evaluation and ranking. The process was built and tested with a significant number of experiments and later evaluated by business experts in a large financial institution where this research was developed. / Organiza??es atuantes nos mais diferentes mercados, t?m utilizado os benef?cios oferecidos pela utiliza??o de t?cnicas de Data Mining DM como atividades complementares a seus sistemas de apoio a decis?o estrat?gica. Por?m, para a grande maioria das organiza??es, a implanta??o de um projeto de DM acaba sendo inviabilizada em fun??o de diferentes fatores como: dura??o do projeto, custos elevados e principalmente pela incerteza quanto ? obten??o de resultados que possam auxiliar de fato a organiza??o a melhorar seus processos de neg?cio. Neste contexto, este trabalho apresenta um processo, baseado no processo de Knowledge Discovery in Database KDD, que visa identificar oportunidades para aplica??o de t?cnicas de DM atrav?s da indu??o e ranqueamento de ?rvores de decis?o geradas pela explora??o semiautom?tica de modelos On-Line Analytical Processing - OLAP. O processo constru?do utiliza informa??es armazenadas em um modelo OLAP preparado com base nas informa??es utilizadas por sistemas de Customer Relationship Management - CRM e Business Intelligence BI, tipicamente utilizados por organiza??es no apoio a tomada de decis?o estrat?gica. Neste trabalho ? apresentada uma s?rie de experimentos, gerados de forma semiautom?tica, utilizando t?cnicas de DM, cujos resultados s?o coletados e armazenados para posterior avalia??o e ranqueamento. O processo foi constru?do e testado com um conjunto significativo de experimentos e posteriormente avaliado por especialistas de neg?cio em uma institui??o financeira de grande porte onde esta pesquisa foi desenvolvida.