A goldmine of valuable tools for data modelers!
Data modelers render raw data-names, addresses, and sales totals, for instance-into information such as customer profiles and seasonal buying patterns that can be used for making critical business decisions. This book brings together thirty of the most effective tools for solving common modeling problems. The author provides an example of each tool and describes what it is, why it is needed, and how it is generally used to model data for both databases and data warehouses, along with tips and warnings. Blank sample copies of all worksheets and checklists described are provided in an appendix.
Companion Web site features updates on the latest tools and techniques, plus links to related sites offering automated tools.
Describes the process of Data Modelling
The book takes you through the process of producing a Data Model - from the point at which you are asked to create a model through to completion. It offers a wealth of practical advice and tools to enable you to create a model that will be fit for purpose.
I use this book in my professional work as a consultant Data Architect and I recommend it to all of my colleagues.
While the early chapters go overboard with meta-meta-meta-data, the latter chapters are truly exceptional. Hoberman's experience doing data models at many firms shows through here, which translates into truly smart advice. Chapters 8 and 9 are gems, and should be required reading for all data modelers.
Excelent practical guide to every junior or intermediate modeler
I loved that book since it is full of practical advices and really justifies its goal of being Modeler's workbench. I use this book often in my daily data modeling practice.
great resource for novice and tenured data professionals
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.
Must have for modelers!
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.
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