Entity-Relationship (ER) Model : MCQs & PYQs with Explanation

Option C

In E–R (Entity–Relationship) modelling, a relationship represents an association among entities. Relationships are classified according to the number of participating entities.

A quaternary relationship involves four different entities participating together in a single relationship.
For example, if we have four entities such as Student, Teacher, Subject, and Classroom, and all four entities participate together in a single relationship, then it is called a quaternary relationship.

Option D

In ER-to-relational mapping, each entity set becomes a separate table. Therefore, entities A and B require two tables.
For relationships:
A one-to-many (1:N) relationship (R1) can be implemented by adding the primary key of entity A as a foreign key in table B, so no separate table is required.
A many-to-many (M:N) relationship (R2) cannot be represented using a foreign key alone, so it requires a separate relation, containing the primary keys of A and B.
Thus, total 3 tables required:

• Table for A.
• Table for B.
• Table for R2.

Option A

In India, each person has only one Aadhaar Card, and each Aadhaar number belongs to only one person.

• Each person can possess only one unique Aadhaar Card.
• Each Aadhaar Card corresponds to exactly one person.

This is a One-to-One (1:1) relationship in the ER Model.

Option A

In a one-to-many relationship, one record in the parent table can be associated with multiple records in the child table. The foreign key is placed in the child table to reference the primary key of the parent table.
In this case, one author can write many books, so the authors table is the parent table and the books table is the child table. Therefore, the foreign key referencing the author’s primary key should be stored in the “books” table.

Option C

A derived attribute is an attribute whose value can be calculated from other stored attributes.

• Age can be derived from Date of Birth.
• Year of services can be derived from Date of Joining.

Option B

In E-R modeling, cardinality defines how many instances of one entity can be associated with instances of another entity.
The statement says, “an entity appears in not more than 5 relationships” this means, one instance of an entity can be related to maximum 5 instances of another entity. This represents a 1:5 relationship.

Option A

A composite attribute is an attribute that can be divided into smaller sub-attributes.
Address can be broken into House No, Street, City, State, and PIN Code, so it is a composite attribute.
Age, City and State are the simple attributes and cannot be meaningfully divided further.

Option B

Generalization is a bottom-up approach where lower-level entities are combined to form a higher-level, more general entity. 

• For example, combining Student and Teacher into a general entity Person.

Specialization is a top-down approach, where a higher-level entity is divided into lower-level entities. 

• For example, Employee is a general entity. It is specialized into Teaching_Employee and Non_Teaching_Employee based on the type of work. This is called specialization because we move from general to specific.

Option A

E-R modeling is primarily a Top-Down approach to database design. It starts with identifying high-level entities and relationships in the real world and then gradually breaks them down into attributes and detailed structures.

Option C

When an E-R model is converted into a relational database, the goal is to represent all data and relationships in the form of tables while maintaining data integrity.
Entities are directly mapped to tables, where:

• Each Entity : Table.
• Each Attribute : Column.

Relationships are handled based on their type:

• 1:1 Relationship : Can be implemented using a foreign key in either table.
• 1:N Relationship : Foreign key is added on the “many” side.
• M:N Relationship : Must be converted into a separate table (called a junction table), which contains foreign keys of both entities.

Note:

• Weak Entities : Become tables and include foreign key of owner entity.
• Composite Attributes : Broken into individual columns.
• Multivalued Attributes : Create a separate table.
• Derived Attributes : Usually not stored in table.

Option D

In data modeling and databases, when two or more objects or entities are related, we care not only about that they are related, but also how many instances of one object can be associated with instances of another.
The number of occurrences of objects (entities) in a relationship is called Cardinality. It defines how many instances of one entity can be associated with instances of another entity. 
For example, in a student-course relationship, one student can enroll in many courses, which represents one-to-many cardinality.

Option B

In database design, an E-R (Entity-Relationship) diagram visually represents entities ("Student", “Employee” or "Course"), their attributes, and relationships between them. Converting this diagram into tables follows specific mapping rules to avoid data redundancy and ensure integrity.
ER-to-Relational Mapping Rules:
When converting an Entity-Relationship (ER) diagram into relational tables, specific rules ensure efficient storage without unnecessary data duplication.
Strong Entity Sets are independent entities that possess their own primary key. Each strong entity set maps to a single table containing all its attributes, with the primary key underlined to indicate uniqueness. This mapping introduces no redundancy since the table stands alone.
Weak Entity Sets represent dependent entities lacking a complete primary key on their own. These map to one table that combines the strong entity's primary key as a foreign key, the weak entity's attributes, and its discriminator. 
Any attributes from the identifying relationship also merge directly into this table, eliminating the need for a separate relationship table.
Strong (Regular) Relationship Sets connect strong entities in many-to-many relationships. These require a dedicated junction table containing the primary keys of both participating entities as foreign keys, along with any relationship-specific attributes.
Weak (Identifying) Relationship Sets establish the ownership link between a weak entity and its parent strong entity. No independent table is created for these, instead, their details, including primary keys and attributes are fully integrated into the weak entity's table. 
Creating a separate table here would be redundant, as the weak entity table already incorporates the owner's primary key to enforce dependency.

Option D

In an ER (Entity–Relationship) Model, an attribute is a property or characteristic of an entity. It tells us something about the entity. Attributes describe the entity with the help of values.
For example, for entity Employee the Name, Age, Salary, Skills and for entity Student the Roll No, Course, Address are attributes.

• Attributes help us store meaningful and organized information about each entity in the system.

Types of Attributes:

Because an employee can have multiple skills, and ER models represent such attributes as Multivalued Attributes.

Option A

A composite attribute is an attribute that can be divided into smaller sub-attributes.
The attribute Name can be broken into First Name, Middle Name, and Last Name, so it is a composite attribute.
Age, City and State are simple attribute and cannot be meaningfully divided further.

Option A

In an ER diagram, a Weak Entity Set cannot be uniquely identified by its own attributes and relies on a Strong (Identifying) Entity Set for uniqueness. The relationship that connects a weak entity to its identifying strong entity is known as the identifying relationship. This relationship is depicted using a Double Diamond symbol.

Since every weak entity must be associated with a strong entity, there is Total Participation, which is represented by Double Lines connecting the weak entity set to the identifying relationship.