Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications [With CDROM]

This book is the perfect blend of project management techniques, application of the software development lifecycle framework, and decision support / business intelligence projects. As a project manager for data mart and decision support projects, I am using this book as a reference for making sure all the steps are covered in these types of projects. All areas are at least touched upon if not covered in greater detail. The authors do an excellent job in explaining many of the BI concepts, identifying steps to completion, and raising questions to consider in tailoring the success of these projects to your organization's circumstances. The deliverables and risks presented for each step fits nicely with the Project Management Institute's PMBOK framework and the tips at the back of the book are incredibly helpful.

It is refreshing to read a book that presents in-depth techniques for developing a BI application from cradle to grave in a continuous evolutionary process. Various matrices and WBS samples in Part II of the book serve as a quick reference for iterative planning and delivering of decision-support systems.The authors have done a phenomenal job in integrating business, technical,and management aspects of a BI and decision-support system to present an exhaustive set of guidelines.After working with numerous clients and having read Inmon's Building the Data Warehouse, Kimball's The Data Warehouse Lifecycle Toolkit as well as various BI white papers, I know that data ETL and data warehouses are a major part of any BI strategy. However, after reviewing the summary of over 20 BI related books, I found that the primary focus of many BI books is normally limited to data presentation and analytical layers only.This book is an exception .I would recommend this book to expert as well as novice DW/BI professionals alike, who may be business users, data analysts, architects, project managers, statisticians,or executive stakeholders.

This is an excellent book and, more importantly, it's very useful. It's loaded with specifics and checklists on what to do and how to do it (it also tells you what not to do). It lays out the pitfalls and tells you how to avoid them. The stages and steps outlined in the book are very specific and the authors, with their wealth of experience, tell you how to implement a successful data warehouse. The work breakdown structure (the tasks you need to implement the data warehouse), the deliverables matrix, and entry and exit criteria for each step are very detailed and alone are worth the price of the book.The book will give those responsible for a data warehouse the information they need to establish best practices within their own organization and will give these folks the ammunition and support to ask for the necessary resources to implement a data warehouse.

Most IT books are dry at best, and really boring at worst. Once again, Larissa Moss has provided a readable, helpful text dealing with a very complex topic. She and Shaku Atre present clear guidelines for seasoned project managers to follow in implementing decision support applications. I thought it was too late to teach an old dog new tricks, but I gathered several ideas that I plan to use on my next big project.Every IT project manager should read this book. While it is intended for BI projects, the more traditional development projects could benefit from the wisdom shared.

There are a number of business intelligence and data warehousing books out in the market today. Most of them have missed the concept of business intelligence road mapping. Larissa Moss and Shaku Atre have put together a great guideline for building a business intelligence system including the risks and pitfalls on every step of the way. In addition, the writers have clearly spent a lot of time researching the subject matter, as it is evident from the deep content as well as the extensive bibliography at the end of each chapter. In my opinion, BI is such a vast and complex process that such research raises the quality of the book as it is describing the experiences and opinions of not just the writers, but also a number of other researchers and experts who specialize in the various sub-fields of business intelligence.I teach a Data Warehousing and BI Class in the Extension section of University of California in Los Angeles, and I will certainly use this book as the text for my class.