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Product Description
Product Description
Read today's business headlines and you will see that many issues stem from people not having the right data at the right time. Data issues don't always make the front page, yet they exist within every organisation. We need to improve how we manage data - and the most valuable tool for explaining, validating and managing data is a data model. This book provides the business or IT professional with a practical working knowledge of data modelling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: know when a data model is needed and which type of data model is most effective for each situation; read a data model of any size and complexity with the same confidence as reading a book; build a fully normalised relational data model, as well as an easily navigable dimensional model; apply techniques to turn a logical data model into an efficient physical design; leverage several templates to make requirements gathering more efficient and accurate; explain all ten categories of the Data Model Scorecard[registered]; learn strategies to improve your working relationships with others; appreciate the impact unstructured data has, and will have, on our data modelling deliverables; learn basic UML concepts; and, put data modelling in context with XML, metadata, and agile development.
About the Author
Steve Hoberman is one of the world's most well-known data modeling gurus. He understands the human side of data modeling and has evangelized "next generation" techniques. Steve taught his first data modeling class in 1992 and since then has educated more than 10,000 people about data modeling and business intelligence techniques. He has presented at over 50 international conferences, authored three data modeling books, founded the Design Challenges group, and invented the Data Model Scorecard(r).
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Customer Reviews
Most Helpful Customer Reviews
2 of 2 people found the following review helpful
Format:Paperback
I know a data modelling trainer who has given hundreds of copies of the first edition of this book to those attending his courses. He did this because it was a great supplement to the material he covered on his training course. Is this second edition a worthy successor?
The author has expanded and restructured the book for this edition; it has grown considerably in size, from 134 to 360 pages. Additional topics have been added, partly based upon the presentations the author makes at seminars and conferences. Some of this additional material has been provided by experts in the respective fields - Bill Inmon, Michael Blaha and Graeme Simsion. This extra material doesn't come for free - the list price has increased two-fold.
This book is a well-scoped and well-written introduction to data modelling and related topics. The author's friendly presentation style really comes across in the text, avoiding the temptation to use geek-speak to impress the reader.
There is no CD included, but there is interaction of a kind, provided by 15 exercises to test your understanding.
I think all the material is great, but I have one minor gripe. In the first edition, there's a separate chapter on the importance of good defiinitions, describing the characteristics of good definitions (clarity, completeness and accuracy). While it is covered in the new book (page 102), it doesn't have the same punch as the original version. Getting people to put the effort into creating good definitions is one of the key challenges with data modelling, so I'd prefer more emphasis.
Should you buy this book?
* If you already have the 1st edition, then you buy the second edition for the extra material; don't throw away the first edition, use it as part of your internal marketing process, by giving it to someone who wants to know what data modelling is about. They'll thank you for it.
* If you're a business or IT person and need to understand more about 'doing' data modelling, buy this book. The first 100 or so pages should be compulsory reading for anyone who has to deal with data models or data modellers.
* If you want to understand more about data modelling without getting into details of 'doing it', consider Data Modeling for the Business: A Handbook for Aligning the Business with IT Using High-Level Data Models (Take It With You), which Steve Hoberman co-authored.
The author has expanded and restructured the book for this edition; it has grown considerably in size, from 134 to 360 pages. Additional topics have been added, partly based upon the presentations the author makes at seminars and conferences. Some of this additional material has been provided by experts in the respective fields - Bill Inmon, Michael Blaha and Graeme Simsion. This extra material doesn't come for free - the list price has increased two-fold.
This book is a well-scoped and well-written introduction to data modelling and related topics. The author's friendly presentation style really comes across in the text, avoiding the temptation to use geek-speak to impress the reader.
There is no CD included, but there is interaction of a kind, provided by 15 exercises to test your understanding.
I think all the material is great, but I have one minor gripe. In the first edition, there's a separate chapter on the importance of good defiinitions, describing the characteristics of good definitions (clarity, completeness and accuracy). While it is covered in the new book (page 102), it doesn't have the same punch as the original version. Getting people to put the effort into creating good definitions is one of the key challenges with data modelling, so I'd prefer more emphasis.
Should you buy this book?
* If you already have the 1st edition, then you buy the second edition for the extra material; don't throw away the first edition, use it as part of your internal marketing process, by giving it to someone who wants to know what data modelling is about. They'll thank you for it.
* If you're a business or IT person and need to understand more about 'doing' data modelling, buy this book. The first 100 or so pages should be compulsory reading for anyone who has to deal with data models or data modellers.
* If you want to understand more about data modelling without getting into details of 'doing it', consider Data Modeling for the Business: A Handbook for Aligning the Business with IT Using High-Level Data Models (Take It With You), which Steve Hoberman co-authored.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
7 reviews
13 of 13 people found the following review helpful
Extremely comprehensive yet still Simple
27 Oct 2009
Format:Paperback
I think very highly of Data Modeling Made Simple (the first edition), so when this second edition came out I had great expectations - which were not only met but also exceeded. Although this second edition is more than twice the number of pages as the first edition, it is still an easy read.
Here are my favorite things about this book:
1. Clearly delivers on its ten objectives. Read the back cover and you will understand the key takeaways you will get after reading the book. After I read the book, I went back over each of these objectives and I was able to check each of these off as accomplished. Everything from justifying the model to building data models to assessing data models was knowledge I gleaned from the book. If you are interested in just one or a subset of these ten objectives, read the Read Me First section and it will reference the sections and chapters you need to read to meet your specific objective.
2. More examples more thoroughly presented. The first edition took a business card example from beginning to end. This edition further expands the business card example and adds several other examples including an ice cream example and many real world examples. The author uses spreadsheets to illustrate many modeling examples, and I too have found spreadsheets to be a very effective way to communicate data and business rules.
3. Data Model Scorecard. The first edition touched on the Scorecard which is the author's technique to reviewing a data model. This second edition goes into detail including providing the template which I can use on my modeling assignments to review my models.
4. Treating a dimensional model as more than just a physical data model. Many texts treat the dimensional as only a physical data model yet there is a business level that this book illustrates at both the subject area and logical levels.
5. Getting other Greats for free. Bill Inmon, Graeme Simsion, and Michael Blaha have all written chapters in this book. I have already starting using Simsion's technique of a diary on my assignments and found it very useful.
My only area for improvement would be to expand the book with more modeling conventions such as ORM and IDEF1X. There is a chapter on UML though that I did find informative. I question however if adding these extra notations would detract from the book's simplicity.
Overall, an excellent read that I would recommend to every business or techie that works with data.
Here are my favorite things about this book:
1. Clearly delivers on its ten objectives. Read the back cover and you will understand the key takeaways you will get after reading the book. After I read the book, I went back over each of these objectives and I was able to check each of these off as accomplished. Everything from justifying the model to building data models to assessing data models was knowledge I gleaned from the book. If you are interested in just one or a subset of these ten objectives, read the Read Me First section and it will reference the sections and chapters you need to read to meet your specific objective.
2. More examples more thoroughly presented. The first edition took a business card example from beginning to end. This edition further expands the business card example and adds several other examples including an ice cream example and many real world examples. The author uses spreadsheets to illustrate many modeling examples, and I too have found spreadsheets to be a very effective way to communicate data and business rules.
3. Data Model Scorecard. The first edition touched on the Scorecard which is the author's technique to reviewing a data model. This second edition goes into detail including providing the template which I can use on my modeling assignments to review my models.
4. Treating a dimensional model as more than just a physical data model. Many texts treat the dimensional as only a physical data model yet there is a business level that this book illustrates at both the subject area and logical levels.
5. Getting other Greats for free. Bill Inmon, Graeme Simsion, and Michael Blaha have all written chapters in this book. I have already starting using Simsion's technique of a diary on my assignments and found it very useful.
My only area for improvement would be to expand the book with more modeling conventions such as ORM and IDEF1X. There is a chapter on UML though that I did find informative. I question however if adding these extra notations would detract from the book's simplicity.
Overall, an excellent read that I would recommend to every business or techie that works with data.
8 of 8 people found the following review helpful
The title is accurate!
15 Nov 2009
Format:Paperback
I have taught data modeling at local colleges from thick, expensive books. I wish I had used this one instead. The examples begin with business cards and ice cream cones -- things people know -- instead of dropping the reader into the middle a major corporation.
The writing style is simple, clean and chatty. Each chapter ends with a list of the key points, so you check yourself. What surprised me is how much he covered without giving you the feeling that you were being buried by too much technical stuff at once.
In short, the title was accurate -- it really did make Data Modeling simple!
The writing style is simple, clean and chatty. Each chapter ends with a list of the key points, so you check yourself. What surprised me is how much he covered without giving you the feeling that you were being buried by too much technical stuff at once.
In short, the title was accurate -- it really did make Data Modeling simple!
7 of 7 people found the following review helpful
Helps You Communicate With Your Business Partner
27 Oct 2009
Format:Paperback
The subtitle, "A Practical Guide for Business and IT Professionals", describes an important reason to read this book. Often it is hard to make Business People understand why a Data Model is as valuable to them as it is to the Database Administrators who will ultimately build the physical database. Steve Hoberman gives us questions to ask the Business that will allow them to fully understand their needs and allow us to capture and communicate those requirements in a form known as a Logical Data Model.
I would recommend this book for those wanting to know more about data models because it is easy to read and understand. At the same time I would recommend it for experienced data professionals because it reinforces and reminds us of the concepts and practices we should all be following as we create our "blueprints" for data.
I would recommend this book for those wanting to know more about data models because it is easy to read and understand. At the same time I would recommend it for experienced data professionals because it reinforces and reminds us of the concepts and practices we should all be following as we create our "blueprints" for data.
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