The authors combine an overview of a data warehouse architecture with a discussion of packaged solutions offered by IBM. Data warehouses are a complex integration of a variety of products. As decision support and analytical processing become more pervasive, the ability to transparently integrate both new and legacy data becomes imperative. Moreover, to complicate this integration, existing installations typically own data managed by several vendors (including nonrelational data). To ease the integration burden, the industry trend is to offer solutions and service support for enterprise-wide decision support systems.

The paper first provides a short synopsis of data warehouse problems, topologies, and objectives. It then discusses relational database management system (RDBMS) warehouse support, middleware, metadata management, and packaged solutions. Finally, the authors address object/relational support and consider where IBM is going next.

The authors’ intention is to give an overview of the architectural infrastructure required to build and manage complex warehouses. This may include centralized or distributed warehouses (with or without data marts) and installations requiring the integration of multiple data stores. The authors focus on IBM solutions and products. They discuss a variety of IBM products, including the relational database family, middleware, replication tools, object support, metadata management, and nonrelational data support.

Overall, the paper’s ideas are well organized and well presented. Its primary audience is business analysts and users of data warehouses. I would recommend it to anyone who wants a high-level overview of data warehouse architectures focusing on IBM solutions and offerings. Those who want an insightful and comprehensive overview of the technical aspects of building a data warehouse should see Inmon [1].