Entity, Attribute, Relationship in DBMS

In a Database Management System (DBMS), especially when using the Entity-Relationship (ER) model, we break down real-world data into entities, describe their properties (attributes), and define how they are related. This helps in organizing and designing a meaningful database structure.

1. Entity

• An entity is a real-world object or concept that can be uniquely identified and stored in a database.
• Entities can be physical (like a student, car, or building) or conceptual (like a course, department, or salary).
• Each entity is represented by a row in a table.

Types of Entities:

• Strong Entity: Has a primary key and exists independently.

• Weak Entity: Does not have a primary key on its own and depends on another entity (usually has a foreign key).

2. Attribute

• An attribute is a property or characteristic of an entity.
• Attributes define data fields in a table and give more information about an entity.
• Each attribute maps to a column in a table.

Types of Attributes:

• Simple (Atomic): Cannot be divided further (e.g., Age, RollNo).

• Composite: Can be divided into subparts (e.g., FullName → FirstName, LastName).

• Derived: Can be derived from other attributes (e.g., Age from Date of Birth).

• Multivalued: Can hold multiple values (e.g., PhoneNumbers).

3. Relationship

• A relationship is an association between two or more entities.
• It describes how entities interact or are linked with one another.
• Represented by a diamond shape in ER diagrams.

Types of Relationships:

• One-to-One (1:1): One entity of A is related to one entity of B.
  Example: Each employee has one unique parking spot.

• One-to-Many (1:N): One entity of A is related to many entities of B.
  Example: One teacher teaches many students.

• Many-to-Many (M:N): Many entities of A are related to many entities of B.
  Example: Students enroll in many courses and each course has many students.

Summary Table

Understanding entities, attributes, and relationships is the foundation of designing ER diagrams and building normalized relational databases. These components ensure data is well-organized, efficient, and reflective of the real world.