Testing the Data Warehouse Practicum: Assuring Data Content, Data Structures and Quality

The quality of a data warehouse (DWH) is the elusive aspect of it, not because it is hard to achieve [once we agree what it is], but because it is difficult to describe. We propose the notion that quality is not an attribute or a feature that a product has to possess, but rather a relationship between that product and each and every stakeholder. More specifically, the relationship between the software quality and the organization that produces the products is explored. Quality of data that populates the DWH is the main concern of the book, therefore we propose a definition for data quality as: "fitness to serve each and every purpose" Methods are proposed throughout the book to help readers achieve data warehouse quality.

Doug Vucevic: Upon an early retirement from the IBM Development Lab in Toronto, where he had worked as a software developer, Doug has been working as an independent consultant to major banks, insurance and retail companies in Toronto, in the field of Software Engineering. Doug's consulting assignments have been in leading quality assurance and testing efforts for: data warehousing, BI and Data Mining in financial, insurance and retail industries. Doug holds Masters' Degree in Electronics and Telecommunication and is a member of the Registered Professional Engineers of the province of Ontario. Wayne Yaddow: Wayne Yaddow has spent more than twenty years developing and testing operating system code at IBM. During the most recent ten years, he devoted his time as an IT consultant, conducting QA on data migration and data integration for large data warehouse projects in the financial industry. While working as a consultant, he shared his data warehousing knowledge with many colleagues on the Internet and in work assignments in New York City.