In the realm of databases, multivalued dependency (MVD) plays a crucial role in defining relationships between attributes. It helps to ensure data integrity and normalization within a database.

What is Multivalued Dependency?

A multivalued dependency occurs when two sets of attributes in a relation have an independent relationship with each other, but not with any other attribute. This means that for every unique combination of the first set of attributes, there can be multiple values associated with the second set of attributes.

Example:

Let’s consider a classic example to understand multivalued dependency better. Suppose we have a relation called Employee with attributes EmployeeID, FirstName, LastName, and Project.

| EmployeeID | FirstName | LastName | Project |
|------------|-----------|----------|---------|
| 1          | John      | Doe      | A       |
| 1          | John      | Doe      | B       |
| 2          | Jane      | Smith    | A       |

Here, EmployeeID (1 and 2) and Project (A and B) form two distinct sets of attributes, and each combination of values represents a unique relationship. The fact that John Doe is associated with both projects A and B is an example of multivalued dependency.

Normalization and Multivalued Dependency

Multivalued dependency can cause data redundancy and inconsistency, violating database normalization principles. To address this, we often decompose the relation into multiple smaller relations using normalization techniques.

Conclusion

Multivalued dependency is a vital concept in database management. It helps identify independent relationships between attribute sets within a relation, ensuring data integrity and normalization. Proper normalization techniques can be employed to eliminate the redundancy and inconsistency caused by multivalued dependency.

#Database #Normalization