Data warehouses have captured the attention of practitioners and researchers alike. But the design and optimization of data warehouses remains an art rather than a science. This book presents the first comparative review of the state of the art and best current practice of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, update propagation, metadata management, quality assessment, and design optimization. Furthermore, it presents a conceptual framework by which the architecture and quality of data warehouse efforts can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence. For researchers and database professionals in academia and industry, the book offers an excellent introduction to the issues of quality and metadata usage in the context of data warehouses. In the second edition, the significant advances of the state of the practice in the last three years are discussed and the conceptual framework is extended to a full methodology for data warehouse design, illustrated by several industrial case studies. 1 Data Warehouse Practice: An Overview --
2 Data Warehouse Research: Issues and Projects --
3 Source Integration --
4 Data Warehouse Refreshment --
5 Multidimensional Data Models and Aggregation --
6 Query Processing and Optimization --
7 Metadata and Data Warehouse Quality --
8 Quality-Driven Data Warehouse Design --