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The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbook is a solution guide to address the business issues in health care 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 health care issues are addressed in this redbook, such as: How to calculate weight for diagnoses related groups? Are there characteristic groups of patients in my population? Can we optimize medical tests for a specific disease? Can we detect precauses for a special medical condition? 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.

The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbook is a solution guide to address the business issues in telecommunications 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 telecoms issues are addressed in this redbook, such as: What are the characteristics of your customers ? Can you predict the customers who are likely to leave? How do you discover the true value of your customers? 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.

The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbook 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 redbook, 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.

The new challenge of integrated solutions is to get more knowledge from data in order to build the most valuable solutions. This IBM Redbook is a solution guide to address the business issues in retail by real usage experience and to position the value of DB2 Intelligent Miner For Data in a Business Intelligence architecture. Typical retail issues are addressed in this redbook, such as: How can I characterize my customers from the mix of products that they purchase? How can I decide which products to recommend to my customers? How can I categorize my customers and identify new potential customers? 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.

Competitive business pressures and a desire to leverage existing information technology investments have led many firms to explore the benefits of data mining technology. This technology is designed to help businesses discover hidden patterns in their data—patterns that can help them understand the purchasing behavior of their key customers, detect likely credit card or insurance claim fraud, predict probable changes in financial markets, and so on. Using Intelligent Miner, you can increasingly leverage the data warehouse and more quickly derive business value from that investment. This redbook will help you design and implement a solution to enhance an existing Business Intelligence environment with the functionality of data mining. It will also help you install, tailor, and configure the Intelligent Miner for Data product on all available platforms. First, we introduce the concepts of Business Intelligence, Data Warehousing, Online Analytical Processing (OLAP), and data mining. We discuss the benefit of data mining and the necessary tasks that must be performed when planning for an implementation of this technology, including such topics as data sources, data transformation, data placement, and security. Next, we introduce the Intelligent Miner for Data product, and describe the environment used at the International Technical Support Organization, including some data mining techniques using this data warehouse. Finally, we provide instructions for installing the product on all available platforms, covering

This redbook is a step-by-step guide to data mining with Intelligent Miner Version 2. It will help customers better understand the usability and the business value of the product. The focus is on helping the Intelligent Miner V2 user determine which algorithms to use and how to effectively exploit them. The business utilized as a case study in the book is a retail bank client of Loyalty Consulting, an IBM business partner based in Toronto, Canada. After a short introduction to data mining technology and Intelligent Miner V2, the case study framework is described. The rest of the book covers each data mining technique in detail and provides ideas on how to implement the techniques. Although no in-depth knowledge of the Intelligent Miner V2 is required, a basic understanding of data mining technology is assumed.

Intelligent Miner for Data enables users to mine structured data stored in conventional databases or flat files. Its mining algorithms have been successfully used by customers and partners alike, to address business problems in such areas as customer relationship marketing and fraud and abuse detection. It allows users to increasingly leverage the data warehouse and more quickly derive business value from that investment. This redbook will help to install, tailor and configure the IBM Intelligent Miner for Data and IBM DataJoiner products to mine any non-IBM data sources. Oracle 8 and two non-relational ODBC data sources -- SPSS and SAS -- have been used to demonstrate DataJoiner acting as a heterogeneous data server for Intelligent Miner in the AIX and Windows NT environments.