Customer Reviews

Data Modeler's Workbench: Tools and Techniques for Analysis and Design

5 star:		(16)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(1)

 

 

Steve Hoberman has written a truly valuable book that is sure to advance the discipline of data modeling. The writing style make it a comfortable and interesting book to read, and the organization makes it useful as a reference. Steve's concepts, definitions, and classification schema help to advance data modeling as a learnable and repeatable process. Many aspects of this book added to my knowledge of data modeling. I learned some new techniques, and I've been a data modeling practitioner since the early 1980's. This is a must for every data modeler's bookshelf. I believe the single greatest impact this book will make is in its attention to data modeling as a human process as well as a technical one.

I bought this book about a month ago based upon a recommendation from a colleague. Technical books don't tend to be the most interesting reading material, but this book with its practical and entertaining format kept me engaged. I have over 9 years of modeling experience (mostly transactional but getting more into data warehousing), and yet I picked up several new techniques. I have already created a Reality Check Subject Area Model of our data warehouse, and am currently working on a Family Tree of several operational systems.

What I liked most about this book was that all the techniques were explained in the order in which they should be applied. For example the subject area analysis techniques were discussed and occur before the subject area modeling techniques. It was very clear how the techniques in the later chapters relied upon the results from techniques in the earlier chapters. I also found the introductions to each of the chapters very entertaining.

This book is incredibly comprehensive. While it provides really useful techniques for technical stuff like analyzing and modeling data, it also covers how to manage the process of modeling--including project planning and the human interactions involved in modeling. That is something so many other computer books leave out.

I just finished reading the Data Modeler's Workbench cover to cover. It is an excellent piece - or as Steve would say, a great story!

I wish I had read this when I first bought it years ago. It would have really helped my modeling career - and I've been a modeler the past seven years.

I think this book is a must read for modelers of any level - from start to finish, not skipping chapters. It nails requirements gathering and analysis, providing templates for capturing same, recognizing that is where the most work lies. I really like the normalization hike and analogy to hiking to the highest peak, then denormalizing and/or abstracting.

It is not a book on theory written by some college professor or glorified lecturer that never or rarely worked in the field; rather, Steve is a tenured data professional who took the time to write down how he does it successfully. Why reinvent the wheel or proceed along in a haphazard way when he lays out how to do it?

Steve also has all the templates on his website, which is a big help.

I have less than one year of data modeling experience and I thought the whole book was a great read, but I got the most out of the discussion on Abstraction in Chapter 9. After reading this chapter, I feel I can spot opportunities to make my modeling structures more flexible. Definitely recommend this book.

I really enjoyed this book. I have been data modeling since 1994 and was able to still pick up some useful techniques. I especially liked the terminology for each of the different tools, like the Normalization Hike and Meta Data Bingo.

I've been waiting for this book! It's an amazing collection of really useful tools and checklists for modeling. And the book is really fun to read. I really enjoyed the examples, and they showed that the author has really learned by doing.

I like the way Steve uses analogies to help us better understand modeling. His introductions to each chapter are both amusing and a great intro to the subject matter in each chapter. His creative way of introducing techniques and the innovativeness of the techniques themselves have had a large impact on the way our department does data modeling. There are two books every data modeler must own: This book and Data Modeling Essentials by Simsion.

The book is based on actual experience as opposed to the theoretical treatment modeling receives in many books.

Steve has shared a lot of practical REAL LIFE checklists which help in extracting domain ... very useful !!!