This is a well-written book, filled with information on various topics related to the project life cycle for decision support systems. The book is divided into two parts: a theoretical foundation part, and a more practical part full of matrices, roadmap/checklist-like elements, and so on. The 16 chapters of Part 1 are organized into six sections: justification, planning, business analysis, design, construction, and deployment.

The chapter on justification refers to the validity of the business case. In the next two chapters, the authors focus on planning, meaning evaluation of the corporate infrastructure, and standard project planning. Business analysis is addressed in four chapters, covering the requirements definition, the data analysis, the application prototyping, and the repository analysis of metadata. The design phase, as defined by the authors, is made of the database design, the design of the repository metadata, and the extract/transform/load (ETL) development. ETL and application development, data mining, and metadata repository development make up the construction unit of he book. Finally, deployment is made up of the implementation and the release evaluation phases.

The book seems to have a very archaic and incomplete approach to the release management/project life cycle, which appears to be an iterative version of the waterfall model. If you are familiar with the V-model, or with the rational unified process (RUP) or any similar methodology, you will find some of the ideas a bit incomplete. For example, there is no indication that you can start your test planning and develop the first test scenarios simultaneously with your requirements management phase. Test management is not given the proper attention, and post delivery support is not brought to the attention of the reader, as a critical area for the success of the project. I also fail to see how one can fruitfully get involved in project planning before the requirement analysis phase, and I do not find these two phases to be mentioned as iterative/reoccurring steps in the book. By the way, you might find that some terminology deviates from the industry standard: for example, post-implementation review is nothing other than the project postmortem.

If you are a software development manager or project manager, and you already follow a specific development or project management methodology, you will find this book of no value to you, since the only new knowledge relating to business intelligence is the excellent “Things To Consider” insert at the beginning of each chapter. I wish the book focused on and expanded this information. You will also find some unnecessary information; there is no need for a chapter dedicated to database design. The level of detail is inconsistent throughout the book; for example, while database design is very extensively covered, testing covers a grand total of less than ten pages. The book also contains certain minor errors, such as introducing time boxing as a method for building application prototypes.

Please note that the title may be a bit misleading, since it creates the expectation that this is a book primarily about the business intelligence area, which it is not. I very carefully reread the authors’ guidelines on “How to Use This Book” and “Who Should Read This Book,” and I still cannot define the audience that would benefit from reading it.

If you are a novice project manager, you might use the book as a reference, assuming that you are not yet committed to a specific project management methodology. However, for an experienced software engineer or manager, the book would probably be of little value.