Business Intelligence and OLAP systems are no longer limited to the privileged few business analysts: they are being democratized by being shared with the rank and file employee demanding a Relational Database Management System (RDBMS) that is more OLAP-aware. DB2 Cube Views and its cube model provide DB2 the ability to address multidimensional analysis and become an actor in the OLAP world. This IBM Redbooks publication focuses on the innovative technical functionalities of IBM DB2 Cube Views V8.1 to store multidimensional metadata in DB2 catalog; to build automatically model-based summary tables to speed up query performance; and to provide an advanced API to allow other Business Intelligence partners’ tools to benefit from both metadata exchange and improved query performance. This book positions the new functionalities and their benefits, so you can understand and evaluate their applicability in your own Business Intelligence and OLAP system environment. It provides information and examples to help you to get started planning and implementing the new functionalities.

Data warehouses in the 1990s were for the privileged few business analysts. Business Intelligence is now being democratized by being shared with the rank and file employee demanding higher levels of RDBMS scalability and ease of use, being delivered through Web portals. To support this emerging e-Business Intelligence world, the challenges that face the enterprises for their centralized data warehouse RDBMS technology are scalability, performance, availability and smart manageability. This IBM Redbooks publication focuses on the innovative technical functionalities of DB2 UDB ESE V8.1 and discusses: This book positions the new functionalities, so you can understand and evaluate their applicability in your own enterprise data warehouse environment, and get started prioritizing and implementing them. Please note that the additional material referenced in the text is not available from IBM.

Today data mining is no longer thought of as a set of stand-alone techniques, far from the business applications, and used only by data mining specialists or statisticians. Integrating data mining with mainstream applications is becoming an important issue for e-business applications. To support this move to applications, data mining is now an extension of the relational databases that database administrators or IT developers use. They use data mining as they would use any other standard relational function that they manipulate. This IBM Redbooks publication positions the new DB2 data mining functions: Part 1 of this book helps business analysts and implementers to understand and position these new DB2 data mining functions. Part 2 provides examples for implementers on how to easily and quickly integrate the data mining functions in business applications to enhance them. And part 3 helps database administrators and IT developers to configure these functions once to prepare them for use and integration in any application. Please note that the additional material referenced in the text is not available from IBM.

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 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 book, 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 Redbooks publication 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 book, 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 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.

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 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 book, 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.