Database normalization

Introduction

Database normalization is a process used in relational database design to organize data to minimize redundancy and improve data integrity. The process involves decomposing a database into two or more tables and defining relationships between the tables. The objective is to isolate data so that additions, deletions, and modifications of a field can be made in just one table and then propagated through the rest of the database via the defined relationships.

A screenshot of a normalized database with multiple tables linked together

History

The concept of database normalization was first introduced by Edgar F. Codd, an IBM researcher, in his 1970 paper "A Relational Model of Data for Large Shared Data Banks". Codd proposed the process as a means to protect the database against certain types of logical inconsistencies that could lead to loss of data integrity.

Normal Forms

Database normalization is typically carried out in stages, referred to as normal forms. Each normal form represents a higher level of normalization, and a database is said to be in a particular normal form if it satisfies a certain set of constraints. There are several normal forms in relational database theory, each with a specific purpose and a set of requirements that a database must meet to comply with it.

First Normal Form (1NF)

A database is in the First Normal Form (1NF) if it satisfies the following conditions:

- Each table has a primary key: a unique identifier for a record in the table. - Each cell in the table contains only atomic (indivisible) values. - There are no repeating or duplicate fields.

Second Normal Form (2NF)

A database is in the Second Normal Form (2NF) if it meets all the requirements of 1NF and the following additional conditions:

- All non-key attributes (columns) in the table must be fully functionally dependent on the primary key. This means that if a column is not part of the primary key, then its value must be determined by the whole key, not by a part of it.

Third Normal Form (3NF)

A database is in the Third Normal Form (3NF) if it meets all the requirements of 2NF and the following additional conditions:

- All non-key attributes must be mutually independent. This means that the value of a non-key column must not depend on the value of any other non-key column.

Boyce-Codd Normal Form (BCNF)

A database is in the Boyce-Codd Normal Form (BCNF) if it meets all the requirements of 3NF and the following additional conditions:

- Every determinant must be a candidate key. A determinant is any attribute on which some other attribute is fully functionally dependent.

Fourth Normal Form (4NF)

A database is in the Fourth Normal Form (4NF) if it meets all the requirements of BCNF and the following additional conditions:

- It must not have any multi-valued dependencies. A multi-valued dependency occurs when one attribute in a table depends on another, yet they are both independent of the primary key.

Fifth Normal Form (5NF)

A database is in the Fifth Normal Form (5NF) or Project-Join Normal Form (PJNF) if it meets all the requirements of 4NF and the following additional conditions:

- Every join dependency in the table is a consequence of the candidate keys of the table.

Benefits of Database Normalization

Database normalization offers several benefits:

- It helps to minimize data redundancy, which in turn reduces the disk space required to store the data. - It helps to maintain data consistency and integrity. - It simplifies the enforcement of referential integrity constraints. - It facilitates efficient data retrieval through more flexible search and sort operations. - It makes the database more flexible to changes in business requirements.

Drawbacks of Database Normalization

Despite its benefits, database normalization also has some drawbacks:

- It can lead to a proliferation of tables. A highly normalized database may require complex join operations to retrieve data, which can impact performance. - It can make the database more difficult to understand and use, especially for inexperienced users. - It may not be suitable for all types of applications. For example, in a data warehousing environment, a denormalized database design may be more appropriate for performance reasons.

Denormalization

Denormalization is the process of combining tables in a database to improve performance. It is essentially the opposite of normalization. While normalization aims to minimize data redundancy and improve data integrity, denormalization aims to improve data retrieval performance at the expense of some data redundancy.

Conclusion

Database normalization is a crucial part of relational database design. It helps to ensure data integrity, minimize data redundancy, and make the database more flexible to changes. However, it also has some drawbacks, and in some cases, denormalization may be a more appropriate strategy.