Mineração de dados em data warehouse para sistema de abastecimento de água

• Ano de defesa: 2009
• Autor(a) principal: Gouveia, Roberta Macêdo Marques
• Orientador(a): Soares, Valéria Gonçalves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraí­ba
• Programa de Pós-Graduação: Programa de Pós Graduação em Informática
• Departamento: Informática
• País: BR
• Palavras-chave em Português: Data Warehouse; OLAP; Data Mining; Sistemas de Abastecimento de Água e Perdas Aparentes
• Palavras-chave em Inglês: Data Warehouse; OLAP; Data Mining; Water Supply Systems and Apparent Losses.
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/tede/6054

This work propose to use technologies of databases with the aim of providing decision support for managers of sector of sanitation, given that the services of water supply for use of the population are a key indicator of quality of life. The fundamental idea is to collect operational data, reduce them to the scope of the problem, organize them into a repository of data, and finally apply the techniques OLAP and Data Mining algorithms to obtain results that give managers a better understanding of the behavior and profile of the company. To facilitate the application of the techniques of Data Mining is necessary that the data are stored properly. Accordingly, an alternative for increasing the efficiency in storage, management and operation of data to support the decision based on the development of Data Warehouse. This is source of strategic information of the business, creating a competitive differential for the company. In this context, was required to implement the repository of data, Data Warehouse, to store, integrate and carry out consultations on the multidimensional data from the company of water supply. Therefore, this Master's thesis aims to design a Data Warehouse relating to Departmental Business, also known as Data Mart; applied the technology on the OLAP multidimensional cubes of data, and run the Data Mining algorithms to the generation of a decision support system to minimize the apparent losses in the urban water supply system.