Market Basket Analysis (MBA) provides the ability to continually monitor the affinities of a business and can help an organization achieve a key competitive advantage. Time Variant data enables data warehouses to directly associate events in the past with the participants in each individual event. In the past however, the use of these powerful tools in tandem led to performance degradation and resulted in unactionable and even damaging information. Data Warehouse Designs: Achieving ROI with Market Basket Analysis and Time Variance presents an innovative, soup-to-nuts approach that successfully combines what was previously incompatible, without degradation, and uses the relational architecture already in place. Built around two main chapters, Market Basket Solution Definition and Time Variant Solution Definition, it provides a tangible how-to design that can be used to facilitate MBA within the context of a data warehouse. Presents a solution for creating home-grown MBA data marts Includes database design solutions in the context of Oracle, DB2, SQL Server, and Teradata relational database management systems (RDBMS) Explains how to extract, transform, and load data used in MBA and Time Variant solutions The book uses standard RDBMS platforms, proven database structures, standard SQL and hardware, and software and practices already accepted and used in the data warehousing community to fill the gaps left by most conceptual discussions of MBA. It employs a form and language intended for a data warehousing audience to explain the practicality of how data is delivered, stored, and viewed. Offering a comprehensive explanation of the applications that provide, store, and use MBA data, Data Warehouse Designs provides you with the language and concepts needed to require and receive information that is relevant and actionable.

Market Basket Analysis (MBA) provides the ability to continually monitor the affinities of a business and can help an organization achieve a key competitive advantage. Time Variant data enables data warehouses to directly associate events in the past with the participants in each individual event. In the past however, the use of these powerful tools in tandem led to performance degradation and resulted in unactionable and even damaging information. Data Warehouse Designs: Achieving ROI with Market Basket Analysis and Time Variance presents an innovative, soup-to-nuts approach that successfully combines what was previously incompatible, without degradation, and uses the relational architecture already in place. Built around two main chapters, Market Basket Solution Definition and Time Variant Solution Definition, it provides a tangible how-to design that can be used to facilitate MBA within the context of a data warehouse. Presents a solution for creating home-grown MBA data marts Includes database design solutions in the context of Oracle, DB2, SQL Server, and Teradata relational database management systems (RDBMS) Explains how to extract, transform, and load data used in MBA and Time Variant solutions The book uses standard RDBMS platforms, proven database structures, standard SQL and hardware, and software and practices already accepted and used in the data warehousing community to fill the gaps left by most conceptual discussions of MBA. It employs a form and language intended for a data warehousing audience to explain the practicality of how data is delivered, stored, and viewed. Offering a comprehensive explanation of the applications that provide, store, and use MBA data, Data Warehouse Designs provides you with the language and concepts needed to require and receive information that is relevant and actionable.

As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that "Building and Maintaining""a Data Warehouse" answers.

Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided.

Organized to logically progress from more general to specific information, this valuable guide-

- Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole

- Examines the concepts and principles that are at the foundation of every successful data warehouse

- Explains how to recognize and attend to problematic gaps in an established data warehouse

- Provides the big picture perspective that planners and executives require

Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.

As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers. Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided. Organized to logically progress from more general to specific information, this valuable guide: Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole Examines the concepts and principles that are at the foundation of every successful data warehouse Explains how to recognize and attend to problematic gaps in an established data warehouse Provides the big picture perspective that planners and executives require Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.