A Toolkit book for your BI Toolbox

As part of a ramp-up plan to get more familiar with the latest Microsoft stack of BI tools and products, a colleague suggested I take a look at The Data Warehouse Toolkit by Ralph Kimball and Margy Ross (ISBN 978-0471200246, on Amazon). I am not going to provide a detailed synopsis of each chapter, you can check the key concepts listed in the text for that, but I want share some thoughts on how I found it useful and an interesting read as well. The book follows a case study format, which helps provide real-world context to the concepts being explained.

If you are new to data warehousing, the first chapter provides all the background and vocabulary you need to get started. This chapter contains explanations and descriptions of facts, dimensions, measures, etc and draws parallels to relational concepts as well.

A four-step design process is laid out early in Chapter 2 and referred to throughout the book. Key here is the notion to select a business process to model. Similar to other database or software development efforts, you need to start with the business requirements first. This is no different in a data warehouse design. The concepts of a data warehouse bus architecture and bus matrix are introduced in Chapter 3. While it’s not exactly the same as an Enterprise Service Bus, occasionally seen in a software solution, there are definitely some parallel ideas.

The case studies in the early chapters start out simple and somewhat generic, but they help illustrate the basic design principals. The more complex case studies in later chapters still provide a good reference for more complex models, techniques, and industry specific scenarios.

A chapter near the end of the book pulls it all together with a project lifecycle description to design and build a data warehouse. Here again, not too different from any other software development effort: gather requirements, design, implement, test, communicate with stakeholders, etc.

Overall, I found the book very useful and plan to keep it handy as a companion reference. I was able to apply some of the modeling techniques directly in a solution leveraging Microsoft SQL Server 2008 Analysis Services, Integration Services and Reporting Services.