Database Normalization

Database Normalization A poor database design can cripple an application, producing problems with redundancy, inaccuracy, consistency, and concurrency of your data. Normalization is a process that serves to reduce, if not eliminate, these problems with data. Since most businesses use 3rd normal form in the logical model, I'll take you through 1st, 2nd, and 3rd NF's. First normal forms requires that there be no multi-valued attributes, and no repeating groups. A multi-valued attribute would contain more than one value for that field in each row. Consider the following StudentCourses table StudentID 12345 54321

Course 3100,3600,3900 1300,2300,1200

In this table, the Course field is a multi-valued attribute. There is not a single value for each field. Now consider this StudentCourses table StudentID 12345 54321

Course1 3100 1300

Course2 3600 2300

Course3 3900 1200

The Course1, Course2, Course3 fields represent repeating groups.

The proper way to store this data follows. First Normal form is satisfied. StudentID 12345 12345 12345 54321 54321 54321

Course 3100 3600 3900 1300 2300 1200

In the first two designs, selecting students that are enrolled in a certain course is difficult. Say I want to do the following

Tell me all of the students enrolled in course 3100. In the first design, you'll have to pull all of the course data and parse it somehow. And in the second design, you'll have to check 3 different fields for course 3100. In the final design, a simple Select StudentID from StudentCourses where Course=3100

Second Normal Form requires that any non-key field be dependent upon the entire key. For example, consider the StudentCourses table below, where StudentID and CourseID form a compound primary key.

StudentID 12345 12345

CourseID 3100 1300

StudentName April April

CourseLocation Math Building Science Building

Grade A B

The Student Name field does not depend at all on CourseID, but only on Student ID. CourseLocation has be dependency on StudentID, but only on CourseID.

This Data should be split into three tables as follows. Students Table StudentID 12345

Name April

Courses Table CourseID 3100 1300

CourseLocation Math Building Science Building

StudentCourses Table StudentID 12345

CourseID 3100

Grade A

12345

1300

B

In this example, grade was the only field dependent on the combination of StudentID and CourseID. Lets suppose that in the first table design, the first row of data was entered with a StudentName of Aprok, a simple typo. Now, suppose the following SQL is run. Delete from StudentCourses where StudentName="April" The erroneous "Aprok" row will not be deleted. However, in the final design, using the following SQL Delete From StudentCourses where StudentID=12345 will delete every course that April was in by using the ID.

Third Normal Form prohibits transitive dependencies. A transitive dependency exists when any attribute in a table is dependent upon any other non-key attribute in that table. Consider the following example CourseSections Table.

CourseID 3100 1300

Section 1 1

ProfessorID 6789 6789

ProfessorName David David

The professor is uniquely identified by the CourseID and Section of the course. However, ProfessorName depends on ProfessorID and has no relation to CourseID or Section. This data is properly stored as follows. Professors Table ProfessorID 6789

ProfessorName David

CourseSections Table CourseID 3100

Section 1

ProfessorID 6789

1300

1

6789

By splitting the data into two tables, the transitive dependency is removed. Taking the original design of the CourseSections table introduces the chance that ProfessorName may be Corrupted. Perhaps on the second row, the ProfessorName is entered as Davif, a simple typo. Since there is no such professor Davif, there is a problem