Customer Reviews

Beginning Relational Data Modeling, Second Edition

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

 

 

I'm really happy with this book. We have needed a practical text on data modeling for some time. The other works have been largely academic. In this book the authors use real world examples to work through the material,

Graphics are used extensively through the book. But that makes sense for the topic. The graphics are a combination of UML and relational diagrams. The tone of the text is jocular and down to earth.

This is an ideal walkthrough for engineers who have some experience using databases but now want to understand how to design databases well.

I've been a database programmer for 15 years but I've never kept up with the "latest" database concepts. Reading Beginning Relational Data Modeling was a great way to get myself up to date! I never learned about conceptual and logical models. So this book was a real eye-opener!

It starts out with a great introduction which includes data normalization. Every developer that works with data should know what the first three are. Apparently there has been another one added called Boyce-Codd Normal Form (BCNF). This one was new to me and I thought it was explained very well.

I thought the book was very informational. I think every developer that works with data should read this book to bring themselves up to data on the latest data modeling concepts.

While the book calls itself "Beginning", it actually takes you a long way into understanding and making a relational model. The authors heavily downplay the formal maths aspect. No predicate calculus and no proving of theorems. Of necessity, the Normal Forms are explained, including the contributions of Boyce and Codd to this development. Simple relational tables are used for illustration. This topic lends itself easily to diagrams of interrelated data sets held in tables. Which is probably more visually understandable anyway.

Perhaps the most important chapter is on making a conceptual model of your system or problem. In a top down approach, you start here. And it can be rather intangible until you build up expertise. Subsequent chapters show how to parlay the conceptual model into a logical model and then into a physical model. Important steps, to be sure, but secondary. Focus on the essentials.

The title should be shortened to just "Relational Data Modeling", as it covers beginner level material, and some advanced topics as well. Some of the concepts presented within are directly applicable in the leading (and expensive) commercial E/R modeling tools.

I thoroughly enjoyed this book. I loved the special historical facts such as the king who had his camels carry his library in alphabetical order for easy retrieval of his favorite books. A metaphor is worth a thousand words. This, in a nutshell, explains data retrieval issues.

The clarity and orderliness in which the steps of normalization were discussed paint a picture of the transformation of raw data into an organized form, its decomposition as well as it's re-composition during de-normalization.

I wish more technical books were written this way.

By the way, it also helped in a completely different area. I was de-cluttering my home and the neatly defined categories in data modeling made this a breeze!

Fun reading!

This is one of the best data modeling books I have read. I was looking for a great introduction to data modeling with good examples and I was not disappointed. Kudos to the authors for a job well done.

Im new to the Data Model and this book helps me to get started.Obviously they covered many areas and in overall examples are pretty good.
Just one complain on the Analysis they took Playing card example which for me tedious I would prefer simple example .Not everyone are expert in Card games.