• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Master's Dissertation
DOI
10.11606/D.18.2016.tde-06052016-143213
Document
Author
Full name
Aline Cazarini Felicio
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2002
Supervisor
Committee
Rebelatto, Daisy Aparecida do Nascimento (President)
Silva, Ethel Cristina Chiari da
Traina, Antonio Fernando
Title in Portuguese
Auxílio do Data Warehouse e suas ferramentas à estratégia de CRM analítico
Keywords in Portuguese
Customer relationship management
Data mining
Data Warehouse
On line analytical process
Sistemas de apoio à decisão
Sistemas de informação
Abstract in Portuguese
Atualmente, uma das grandes vantagens competitivas que uma empresa possui em relação a seu concorrente é a informação sobre seu cliente. As estratégias de Customer Relationship Management (CRM), propiciam o profundo conhecimento do cliente, para que a empresa possa tratá-lo de forma personalizada e reconhecê-lo como seu principal patrimônio. Segundo TAURION (2000) e DW BRASIL (2001), para suportar essa tecnologia, é necessário que as empresas possuam um repositório de dados históricos de clientes. O Data Warehouse (DW) possui diversas características que utilizam, de forma adequada e eficiente, ferramentas de desenvolvimento de modernos bancos de dados. Através da ferramenta Data Mining (DM), é possível descobrir novas correlações, padrões e tendências entre informações de uma empresa pela extração e análise dos dados do DW. A análise dos dados também pode ser feita através de sistemas On Line Analytical Proccess (OLAP), os quais ajudam analistas a sintetizar informações sobre as empresas, por meio de comparações, visões personalizadas, análise histórica e projeção de dados em vários cenários. Diante deste contexto, parece possível afirmar que o DW, juntamente com o OLAP, podem proporcionar grande suporte à estratégia de CRM. Desta forma, esta pesquisa apresenta como objetivo identificar e analisar as principais contribuições que o DW e suas ferramentas podem dar à estratégia CRM Analítico.
Title in English
The helpful that DW and your tools can give to the strategy of CRM analytic
Keywords in English
Customer relationship management
Data mining
Data Warehouse
Decision support systems
Information systems
On line analytical process
Abstract in English
Nowadays, the great competitive advantage that a company possesses in relation to your competitor is the information about its customer. The strategies of Customer Relationship Management (CRM) provide deep knowledge about the customer, so that the company can treat them in a personalized way and it recognizes them as its main patrimony. According to TAURION (2000) and DW BRASIL (2001), to support that technology, it is necessary that the companies possess a repository of customers' historical data. Data Warehouse (DW) possesses several characteristics that use, in appropriate and efficient way, tools of development of modern databases and, through the too Data Mining (DM) discovers new correlations, pattems and tendencies among information of a company, for the analysis of the data of DW. The analysis of the data can also be made through the systems On Line Analytical Proccess (OLAP), which help analysts and executives to synthesize information on the companies, by means of comparisons, personalized visions, historical analysis and projection of data in several sceneries. In this context, it can be stated that DW and DM can provide great support to the strategy of CRM. Thus, this work presents as objective to identify the main contributions that DW and their tools can give to the strategy of Analytical CRM.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
Publishing Date
2016-05-06
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
CeTI-SC/STI
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2021. All rights reserved.