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.
Table of Contents
Data Warehouse ROI
What is Market Basket Analysis?
How does Market Basket Analysis produce ROI?
Why is Market Basket Analysis difficult?
Market Basket Solution Definition
Database Design Strategies
ETL into a Market Basket Datamart
What is Time Variance?
How does Time Variance produce ROI?
Time Variant Solution Design for Type 1 and 2 Time Variant Data
Database Design Strategies
ETL into a Time Variant Data Warehouse
Combine Time Variant Design with Market Basket Analysis
Fon Silvers is a Data Warehouse ETL Analyst and Data Warehouse Support Team Lead in a Fortune 500 company. His first book was Building and Maintaining a Data Warehouse. Fon can be found at LinkedIn (http://www.linkedin.com/in/fonsilvers) and his Amazon Author page (http://www.amazon.com/FonSilvers/e/B001JRVJMG/ref=ntt_athr_dp_pel_pop_1).