A functional dependency occurs when the value of one attribute (or a set of attributes) uniquely determines the value of another attribute. This relationship is denoted as:
X → Y
Here, X is the determinant, and Y is the dependent attribute. This means that for each unique value of X, there is precisely one corresponding value of Y.
Consider a table named Students with the following attributes:
| StudentID | StudentName | StudentAge |
|---|---|---|
| 101 | Rahul | 23 |
| 102 | Ankit | 22 |
| 103 | Aditya | 22 |
| 104 | Sahil | 24 |
| 105 | Ankit | 23 |
StudentID
StudentName
StudentAge
101
Rahul
102
Ankit
103
Aditya
104
Sahil
105
Ankit
The above table has the following functional dependencies
StudentID → StudentNameStudentID → StudentAge
StudentID → StudentNameStudentID → StudentAge
Note that the functional dependencies StudentName → StudentAge or StudentAge → StudentName Do not hold.
- Functional dependency is expressed in the form of equations. For example, if we have an employee record with fields “EmployeeID”, “FirstName” and “LastName” we can specify the function as follows:
EmployeeID → FirstName, LastName
EmployeeID → FirstName, LastName
- To represent functional dependency in DBMS has two main features: left (LHS) and right (RHS) of the arrow (→).
- For example, if we have a table with attributes “X”, “Y” and “Z” and the attribute “X” can determine the value of the attributes “Y” and “Z”.
X → Y, Z
X → Y, Z
- This symbol indicates that the value in property “X” determines the values in property “Y” and “Z”. So if you know the value of “X”, you can also determine the value of “Y” and “Z”.
The concept of normalization is based on functional dependencies. Using functional dependencies, we break a table in multiple tables that helps us in preventing duplicate data and hence Improves Data Quality, less errors and better database design.