How DBMS Reduces Data Redundancy?

Answer: DBMS reduces data redundancy by using the techniques of normalization and the concept of primary and foreign keys.

Database Management Systems (DBMS) play a crucial role in minimizing data redundancy, which optimizes storage, improves data integrity, and simplifies data management.

Normalization Techniques

DBMS uses normalization to organize data into well-structured tables, minimizing redundancy. This involves breaking down large tables into smaller ones and establishing relationships between them.

Primary Keys

By introducing primary keys in tables, DBMS ensures each record is uniquely identified. This eliminates duplicate entries and enhances data integrity.

Foreign Keys

Relationships between tables are established using foreign keys. This prevents the need for repeating data in multiple tables, reducing redundancy while maintaining connectivity.

Data Modeling

Proper data modeling techniques, such as Entity-Relationship (ER) diagrams, help in identifying and eliminating redundant data. Entities and their attributes are represented systematically, reducing redundancy.

Use of Views

DBMS allows the creation of views, which are virtual representations of data based on specific queries. Views help present data without physically duplicating it, reducing redundancy in result sets.

In essence, DBMS acts as a data guardian, ensuring information is stored efficiently and accurately, empowering businesses to make informed decisions based on reliable data.