1.1. Brief Background of Conceptual Data Modeling

What, Not How

The most important aspects to remember about conceptual data models is that

• they are graphical diagrams that depict what data someone wants to remember and store in a database for later analysis;

• they do not indicate how that data is to be stored;

• they therefore are at the most abstract level of detail about the underlying database.

This book will depict fragments of very simple conceptual data models using Logical Data Structure (LDS) notation, as presented in:

Mastering Data Modeling, A User-Driven Approach, by John Carlis and Joseph Maguire. Addison-Wesley Professional, 2000. ISBN 9780134176536

Conceptual data models are an excellent tool for use with end users, so that you get the essence of what data they have without worrying about implementation details. When modeling, we want to avoid thinking about implementation as much as possible. However, knowing a bit about the underlying implementation of a relational database will help you see why many excellent guidelines suggested in this above book have become good practice for creating models– they make it easy to create relational databases directly from the conceptual model and its associated sample data instances you obtain from working with users.

1.2. Transition from Conceptual Models to Implementation

In this first part of this book we will start to think as practitioners by learning a bit about database implementation as we practice how to work with users on the conceptual modeling task. The next few chapters are intended as a companion to the above book or one like it in which you are practicing and mastering data modeling.

This part of the book is likewise a stepping stone to part 2, where we will examine how we extract information from the databases we have been able to create.

You have attempted of activities on this page