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Mining your own business in banking : using DB2 Intelligent Miner for data.

The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbooks publication is a solution guide to address the business issues in banking by real usage experience and to position the value of DB2 Intelligent Miner For Data...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: International Business Machines Corporation. International Technical Support Organization
Otros Autores: Baragoin, Corinne
Formato: Electrónico eBook
Idioma:Inglés
Publicado: San Jose, Calif. : IBM Corp. International Technical Support Organization, 2001.
Edición:1st ed.
Colección:IBM redbooks.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

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520 |a The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbooks publication is a solution guide to address the business issues in banking by real usage experience and to position the value of DB2 Intelligent Miner For Data in a Business Intelligence architecture as an integrated solution. Typical banking issues are addressed in this book, such as: How can you discover the characteristics of your customers? Which products can you sell to which customers and how? This book also describes a data mining method to ensure that the optimum results are obtained. It details for each business issue: - What common data model to use - How to source the data - How to evaluate the model - What data mining technique to use - How to interpret the results - How to deploy the model Business users who want to know the payback on their organization when using the DB2 Intelligent Miner For Data solution should read the sections about the business issues, how to interpret the results, and how to deploy the model in the enterprise. Implementers who want to start using mining techniques should read the sections about how to define the common data model to use, how to source the data, and how to choose the data mining techniques. 
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