Database Normalization

Database Normalization

This paper outlines the normalization process for the Fleet Truck Maintenance database. There are seven levels of normalization and each level is built on the previous level. The Fleet Trunk maintenance database has 5 tables' employee, maintenance, annual inspections, vehicles, and repairs. This paper will discuss the first, second, and third levels of normalization of the employee table. The Fleet Trunk Maintenance database is configured in the third normal form which is the most common form of database normalization. Each normalization level contains rules.

First, the employee database was arranged in the first normal form as follows:

1. Contain a unique name in each column.

2. All columns must have a single data type.

3. No identical values in two rows.

4. A single value in each column.

5. No repeating groups in columns.

Second, the employee table was arranged in the second normal form as follows:

1. It is in 1NF

2. All of the non key fields depend on all of the key fields.

The employee table contained vehicles and maintenance. Vehicles and maintenance were removed and place in a new table with a primary key and the table was developed.

Third, the employee table was arranged to the third normal form as follows:

1. It is in second normal form.

2. Its only determinates are primary keys.

All the dependent fields were taken out of the employee table and placed in new tables. The primary key is now the foreign key in the vehicle and maintenance tables. Each table is independent and a relationship can be established with each table by the primary key.

Finally, normalization makes a relational database flexible and provides easy changes in the structure of the data. A database can encounter various anomalies such as duplicated data, inability to delete data without deleting important data, and unnecessary data. Database normalization is necessary to guard the database from certain sorts of inaccuracy and improve the database design.

Reference

Kroenke, D. M., & Auer, D. J. (2012). Database Concepts (4th ed.). AR: Prentice Hall.