How to get the Most out of this Book
Here is a suggested approach to leveraging this book based upon your data modeling and ER/Studio experience:
|
Data Modeling Experience |
ER/Studio Experience |
Suggested Approach |
|---|---|---|
|
Little or None |
Little or None |
Start at the beginning of the text and read through Chapter 10 on Physical Data Models (Sections I through III). Make sure you do all of the data modeling and ER/Studio exercises, and save Section IV for after you get comfortable with basic ER/Studio functionality. |
|
Good or Great |
Little or None |
You can skip Chapter 1 and go straight to Chapters 2 and 3 to get comfortable with the ER/Studio landscape. Then in each of the chapters in Sections II and III, briefly scan the data modeling concepts sections and focus on the ER/Studio-specific sections. Save Section IV for after you get comfortable with the basic ER/Studio features. |
|
Good or Great |
Good or Great |
You can treat this book as a reference, and whenever you need a refresher in a certain topic, you can use the table of contents and index to find that topic. Make sure you read about the latest features of ER/Studio in Chapter 2 and read the feature chapters from Section IV. |
This book will explain data modeling and how to use ER/Studio, while still maintaining the spirit of keeping it simple. To keep it simple required resisting the temptation to go into more detail than necessary and saving the more advanced stuff for the ER/Studio User Guide that comes with the product.
I am a firm believer in the 80/20 rule – you can learn 80% of data modeling and ER/Studio functionality in 20% of the time, and then learn the remaining 20% you need to know over time by practicing with the tool, and by taking on more and more challenging data modeling assignments.
I am also a firm believer in playing. We might as well have fun learning, so throughout the book, feel free to play with the buttons and menus and see what happens – you can always hit the undo button or close your data model without saving it.
Data modeling is more than a job or a career – it is a mindset, an invaluable process, a healthy addiction, a way of life. Remember to Keep It Simple, and enjoy the ride!
