Customer Reviews

The Data Warehouse Lifecycle Toolkit

5 star:		(38)
4 star:		(15)
3 star:		(0)
2 star:		(0)
1 star:		(4)

 

 

but were afraid to ask. This is the definitive book on the DW lifecycle. After having worked on two not-so-perfect data warehousing projects, I found myself on more than one occasion seeing in print many of the ideas that I have either arrived at by trial and error or had a hunch were the right way to go. I would have given this book five stars, except for one thing: you really need to have read Kimball's first book, The Data Warehouse Toolkit, to get the proper foundation for reading the DW Lifecylcle Toolkit. I bought the DW Lifecycle Toolkit first thinking that I could jump right ahead. Not so. Much to my chagrin, I ended up buying the DW Toolkit and reading it first. These books really should be offered with the option to be purchased together. That way, the reader will know up front that both books are a must read.

Not enough examples....they keep referring to other books. The book would've been awesome if it had more examples (specially designing star schema models and aggregations). I don't like to spend $40-50 each on two books just to get the examples and lot of the repeat information. The book companies and the authors are making more money by doing this, but they're not winning fans (Wiley books and Kimball)

Our organization has implemented a very successful Data Warehouse, due largely to following the design and deployment principles from Dr. Kimball's two textbooks. The key to a successful Data Warehouse is providing all business users an easy to use and high performance queryable system. The dimensional design is, without a doubt, the defacto standard for Queryable Data Warehouses, and the author does a superb job motivating its use and explaining how to develop your integrated, dimensional data warehouse. In addition, the author gives valuable advice on many, many other aspects of the process, such as assessing your readiness for proceeding with a warehouse effort. This book is a "must read" for anyone involved in a Data Warehouse project. You will have an excellent chance of succeeding with even a most complicated Data Warehouse System if you follow the wisdom in this book.

PROS
- Offers invaluable advice based on the authors' experience so that you don't need to re-invent the wheel or make the same mistakes they made (and subsequently learned from).
- Most useful for Project Managers/DBAs; less so for Data Modellers.

CONS
- I purchased this book on the assumption that it offered a comprehensive treatment of all stages of the Data Warehouse project lifecycle (as the cover would lead you to believe). However, it does not offer a comprehensive treatment of Dimensional Modelling. For this, the book actually assumes you have read Kimball's former book - "The Data Warehouse Toolkit - The Complete Guide to Dimensional Modeling" (which provides a full treatment and practical examples for several industry sectors).
- I did not like the writing-style. If the authors would have omitted all text like "we believe.." and "in our experience..." I'm sure the book wouldn't have used 800 pages.

CONCLUSION
This book has remained by my side throughout the project lifecycle, giving great guidance and pointers to help manage the project optimally.
However, if you are responsible for Data Modelling, you will also need to buy "The Data Warehouse Toolkit", thereby doubling the overall cost.

We were at a lose on how to proceed with putting together an historical database that would track 10,000 discrete survey items from over 800 surveys per year, including survey indications, and official estimates. The real problem was doing it such a way as to make it easy to use, understandable, and accessible to all of our data analysts. We read Inmon's book and decided it would be too complicated and slow if we used his approach. Besides, we wanted true ad-hoc capabilities, and did not want to be hampered by a system that had too little data, or was being controled by someone trying to save nickles on DASD by spending dollars of our time. Kimball's book gave us what we were looking for: a way to build a data warehouse incrementally, using and tracking the lowest level of granularity in our data, and offering simplicity and service without an army of IT consultants. His engineering approach to dimensional modeling, particularly his notion of conforming dimensions puts the traditionalists, like Inmon, out to pasture.

I wish Kimball would get off his anti-relational & E/R kick. Yes star schema provides the most efficient and understandable design for datamarts, as people tend to think dimensionally and hierarchicly. But 'dimensional modelling' is just de-normalization for performance and understandability. If your staging area or ODS is not 3NF, you haven't a hope of resolving cross-deparmental issues and coming up with enterprise query capability. To balance Kimball's viewpoint you must read something like 'Data Stores, Data Warehousing and the Zachman Framework' as well.

Ralph and his colleagues wrote a wonderful book about Data Warehousing. Ralph's objective is to make user happy. He want's to build intuitive and user-friendly Data Warehouses with a good performance and in this book he tells us how to succeed. He guides you through the Data Warehouse process form initialize interviews to design staging area and dimension models and lots more. I found this book to be the perfect answer to bringing myself up to speed. Not too technical -- but enough information to answer all the important questions which can occur in a Data Warehouse project Easy reading as well for people who native language is not english. Just read it and lets make users happy.

By the why: I would like to recommend this book to NCR's Rob Armstrong.

This book is terrific. I've been involved in implementing a data warehouse, and I wish I'd had this book then, as the author proposes solutions to several problems we encountered, but had less elegant, or no, solutions for. I have read a number of books on data warehousing, and a major portion of every one of them is devoted to the politics of getting management to adopt, and then support, building a data warehouse, and very little on the concrete aspects involved. This book is almost entirely on the nuts and bolts of actual doing the implementation, assuming it is already supported by management. Presents how to do dimensional (star schema) models from elementary to highly advanced. Every important aspect of implementing a data warehouse is covered with real content at all points. Wonderful resource book for the experienced warehouse person, while also extremely helpful the the novice, and anyone in between. Read this book first, then peruse any others in the book store before buying--you may not need a second book.

After 21 years in software development, which includes managing three data warehouse projects, I had decided to write a book trying to capture whatever wisdom I had accumulated. After reading this book I no longer feel the need to.

This book not only provides detailed techniques for building a data warehouse and managing the process, it also deals with the realities faced in these projects. If you've ever been frustrated with those abstract tomes written by strict methodologists while you were burdened with a tight budget, a dysfunctional company (is that redundant?), immature technology, underskilled technologists and waffling user support -- then this is the book for you. It is filled with recommendations for conducting every phase of the project, yet is always careful to acknowledge that no two projects are alike and there is no one guaranteed blueprint for managing the project.

My only regret is that this book wasn't available before my first data warehouse projects. Although our teams ended up at many of the same conclusions, it was only after a lot of hard thought, insecurity, and trial and error.

If you are going to develop a data warehouse or a data mart, read this book first.

This book is the second in a series from the author and more concisely describes not only data warehouse methods, but also the pitfalls. Most people unfamiliar with data warehousing methods think it is simply "cloning" data. As the president of a company who implements data warehouses, we concur with Mr. Kimball and the fact that data warehousing is a "process" and the users of the data warehouse are the single most important criteria to building it. Mr. Kimball takes you through the difficult task of determining your "readiness" for a data warehouse and walks you through the entire process. This book is not for novices, but rather for the experienced individual(s) interested in exploring methods for implementing a solution that historically has at least a 50% chance of failure before it even begins. This book is an architects blueprint, crystalizing the reasons for such a high failure rate and how to avoid the common pitfalls. It won't build the data warehouse for you, but it should be mandatory reading for anybody involved in a data warehouse project.