Database normalization is the process of organizing the attributes of the database to reduce or eliminate **data redundancy (having the same data but at different places) **.

**Problems because of data redundancy**

Data redundancy unnecessarily increases the size of the database as the same data is repeated in many places. Inconsistency problems also arise during insert, delete and update operations.

**Functional Dependency**

Functional Dependency is a constraint between two sets of attributes in a relation from a database. A functional dependency is denoted by arrow (→). If an attributed A functionally determines B, then it is written as A → B.

For example, employee_id → name means employee_id functionally determines the name of the employee. As another example in a time table database, {student_id, time} → {lecture_room}, student ID and time determine the lecture room where the student should be.

**What does functionally dependent mean?**

A function dependency A → B means for all instances of a particular value of A, there is the same value of B.

For example in the below table A → B is true, but B → A is not true as there are different values of A for B = 3.

A B ------ 1 3 2 3 4 0 1 3 4 0

**Trivial Functional Dependency**

X → Y is trivial only when Y is subset of X.

Examples

ABC → AB ABC → A ABC → ABC

**Non Trivial Functional Dependencies**

X → Y is a non trivial functional dependencies when Y is not a subset of X.

X → Y is called completely non-trivial when X intersect Y is NULL.

Examples:

Id → Name, Name → DOB

**Semi Non Trivial Functional Dependencies**

X → Y is called semi non-trivial when X intersect Y is not NULL.

Examples:

AB → BC, AD → DC

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above

Attention reader! Don’t stop learning now. Get hold of all the important CS Theory concepts for SDE interviews with the **CS Theory Course** at a student-friendly price and become industry ready.