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Chapter 4 - Normalizing a Data Model

Posted by Addison Wesley Free Book | C# Language September 01, 2009
Data normalization is probably one of the most talked-about aspects of database modeling. Before building your data model, you must answer a few questions about normalization. These questions include whether or not to use the formal normalization forms, which of these forms to use, and when to denormalize.
 

This chapter has been excerpted from book "A Developer's Guide to Data Modeling for SQL Server" with permission from Addison-Wesley"
 
 NORMALIZING A DATA MODEL
 
 Data normalization is probably one of the most talked-about aspects of  database modeling. Before building your data model, you must answer a  few questions about normalization. These questions include whether or not to use the formal normalization forms, which of these forms to use, and when to denormalize.
 
 To explain normalization, we share a little bit of history and outline the most commonly used normal forms. We don't dive very deeply into each  normal form; there are plenty of other texts that describe and examine every detail of normalization. Instead, our purpose is to give you the tools necessary to identify the current state of your data, set your goals, and normalize (and denormalize) your data as needed.
 
What Is Normalization?
 
At its most basic level, normalization is the process of simplifying your data into its most efficient form by eliminating redundant data. Understanding the definition of the word efficient in relation to normalization is the key concept. Efficiency, in this case, refers to reducing complexity from a logical standpoint. Efficiency does not necessarily equal better performance, nor does it necessarily equate to efficient query processing. This may seem to contradict what you've heard about design, so first let's walk through the concepts in normalization, and then we'll talk about some of the performance considerations.
 
Normal Forms
 
E. F. Codd, who was the IBM researcher credited with the creation and evolution of the relational database, set forth a set of rules that define how data should be organized in a relational database. Initially, he proposed three sequential forms to classify data in a database: first normal form (1NF), second normal form (2NF), and third normal form (3NF). After these initial normal forms were developed, research indicated that they could result in update anomalies, so three additional forms were developed to deal with these issues: fourth normal form (4NF), fifth normal form (5NF), and the Boyce-Codd normal form (BCNF). There has been research into a sixth normal form (6NF); this normal form has to do with temporal databases and is outside the scope of this book.
 
It's important to note that the normal forms are nested. For example, if a database meets 3NF, by definition it also meets 1NF and 2NF. Let's take a brief look at each of the normal forms and explain how to identify them.

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