Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves breaking tables into smaller tables and linking them through relationships. The goals are to eliminate storing duplicate data, ensure related data is stored together, and reduce data anomalies. Normalization is achieved through three normal forms - 1NF, 2NF, and 3NF - which introduce rules to simplify attributes, eliminate partial dependencies, and remove transitive dependencies.

1. NORMALIZATION

2. Normalization
 Normalization is the process of efficiently
organizing data in a database.
 Normalization is the process of applying a
series of rules to ensure that your database
achieves optimal structure.

3. Why we do Normalization?
 There are two goals of the normalization process:
1- eliminating redundant data
For example: storing the same data in more than
one table
2- ensuring data dependencies make sense.
For example: only storing related data in a table.
Both of these are worthy goals as they reduce the amount of
space a database consumes and ensure that data is logically
stored.

4. Database Anomalies:
 Repetition Anomaly
 Insertion Anomaly
 Deletion Anomaly
 Updating Anomaly

5. First Normal Form (1NF)
 Each attribute must be atomic
• No repeating columns within a row.
• No multi-valued columns.
 1NF simplifies attributes
• Queries become easier.

6. 1NF
Employee (unnormalized)
emp_no emp_name project_id project_name grade salary
142 John 113, 124 blue star, magnum A 20,000
168 James 113 blue star B 15,000
263 Andrew 113 blue star C 10,000
Employee (1NF)
emp_no emp_name project_id project_name grade salary
142 John 113 blue star A 20,000
142 John 124 magnum A 20,000
168 James 113 blue star B 15,000
263 Andrew 113 blue star C 10,000

7. Second Normal Form (2NF)
 Each attribute must be functionally
dependent on the primary key.
• Partial Functional dependency – a non-key attribute
should not be partially(functionally) dependent on
more than one key attribute.
• Any non-dependent attributes are moved into a
smaller (subset) table.
 2NF improves data integrity.
• Prevents update, insert, and delete anomalies.

8. Functional Dependency
Emp_name, grade and salary are functionally
dependent only on emp_no. (emp_no -> emp_name,
grade, salary)
Project_name is dependent only on project_id.
But these table should be related through foreign
keys.
emp_no emp_name grade salary
142 John A 20,000
168 James B 15,000
263 Andrew C 10,000
109 Bob C 10,000
Employee (1NF) Project (1NF)
project_id project_name
113 blue star
124 magnum

9. 2NF
emp_no emp_name grade salary
142 John A 20,000
168 James B 15,000
263 Andrew C 10,000
109 Bob C 10,000
Employee (2NF)
Project (2NF)
project_id project_name
113 blue star
124 magnum

10. Data Integrity
• Insert Anomaly - adding null values. eg, inserting a
new project does not require the primary key of emp_no
to be added.
• Update Anomaly - multiple updates for a single name
change, causes performance degradation. eg, changing
magnum project_name to meganum.
• Delete Anomaly - deleting wanted information. eg,
deleting the magnum project removes employee John
personal info from the database.

11. Third Normal Form (3NF)
Remove transitive dependencies.
•Transitive dependency – if an attribute can be
determined by another non-key attribute.
• Any transitive dependencies are moved into a
smaller (subset) table.
3NF further improves data integrity.
• Prevents update, insert, and delete anomalies.

12. Transitive Dependency
salary is determined by grade and not the key
attribute emp_no.
Thus this transitive dependency needs to be
removed, and grade and salary are moved to another
table.
emp_no emp_name grade salary
142 John A 20,000
168 James B 15,000
263 Andrew C 10,000
109 Bob C 10,000
Employee (3NF)

13. 3NF
emp_no emp_name grade
142 John A
168 James B
263 Andrew C
109 Bob C
Employee (3NF) Project (3NF)
project_id project_name
113 blue star
124 magnum
Employee Project(3NF)
emp_no project_name
142 113
142 124
168 113
263 113
109 124
Grade Salary(3NF)
grade salary
A 20,000
B 15,000
C 10,000

14. Denormalization
 Denormalization is a technique to move from
higher to lower normal forms of database
modeling in order to speed up database
access.