I believe I bought this book a week or two after it came out (January 2008) with the intention of reading it immediately. Unfortunately, life happens and I have no idea what came up but I’m sure it was good. And, to be honest, I’m somewhat happy that whatever it was did come up because this was a good time for me to read through this.
I started reading this book in 20 August 2011 and finished it 11 September 2011. Oddly enough, I started this just prior to being told that the data warehousing project that we are planning at my current employer may be coming along a bit more quickly than originally thought. As such, I’m ramping up on some refresher material and this was perfect for that need. (I’m also thinking that I’ll be refreshing my SSRS / SSAS and that I might take a stab at the MCITP 70-452 Business Intelligence Developer exam)
As some background information, I have read several other Kimball Group books, including:
- The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition)
- which is thoroughly dog-eared and highlighted; a rather rare occurrence for me.
- The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data
- The Microsoft Data Warehouse Toolkit: With SQL Server 2005 and the Microsoft Business Intelligence Toolset.
If you have read more than one of these books you will realize that there is a lot of material that overlaps between them but that each has its’ own focus. The focus of the Lifecycle Toolkit seemed to me to be on the project manager, or at least on giving an overview of the process as a whole. It seemed to me to be more of a “whet the appetite” with the ability to dive in more expansively through some of the other books referenced above. What The Data Warehouse Lifecycle Toolkit provided more than any of the others listed above was to give a good list of all of the tasks that will be required (or at least recommended) to complete a Data Warehouse project. I believe that a good portion of the text was set aside to drive home how much work is really involved and that this is not a trivial task. It continuously mentioned brining in the business, and having the project manager read through what was required in each of the major steps so that this could be conveyed back up the chain.
With that said, this book was a somewhat generic introduction to the topic at hand and no one topic was pursued in depth to the point that you would have all of the knowledge necessary to be an expert. However, it provided lots of great information relating to the relevant portions of the project, from preparing the project definition, to gathering the key players, to what is really necessary for the business requirements and how you can begin to put them together, etc. There is also lots of information relating to the dimensional modeling, the ETL subsystems, data profiling, data quality and the B.I. presentation layers.
As such, I’d recommend The Data Warehouse Lifecycle Toolkit to anyone looking to get involved in a Data Warehouse Project, particularly if you are going to be expected to be in a leadership role on the project. If you are to be involved as a data modeler or an ETL Developer and are a bit strapped for time it might be more advantageous to skip this volume and go straight to The Data Warehouse Toolkit followed by The Data Warehouse ETL Toolkit. (Alternately, you can start with the Microsoft Toolkit if that is the technology stack you will be using).