Free Mock Test : DBMS (Database Management System) : Data modeling (Test 2)

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Free Mock Test - DBMS (Database Management System) : Data modeling (Test 2)

In recent years, Data Modeling in DBMS (Database Management System) has emerged as a crucial topic for candidates preparing for competitive and officer-level examinations, including banking, SSC, and technical recruitment tests. Experts suggest that a strong understanding of data modeling concepts can significantly improve problem-solving accuracy and overall scores.
Data modeling refers to the process of structuring and organizing data using models such as the Entity-Relationship (ER) Model, Relational Model, and Hierarchical Model. Among these, the Relational Model remains the most widely tested concept, focusing on tables, keys, constraints, and relationships between data.
Examination trends indicate that questions are increasingly designed to test not only theoretical knowledge but also practical understanding. Topics like primary key, foreign key, normalization, entity relationships, and constraints are frequently asked in moderate to high-difficulty levels. Candidates are often required to analyze scenarios, identify relationships, and apply normalization rules.

Total Questions : 20

Timer : sec

Question : In generalization, the resulting higher-level entity is called:

Subclass

Superclass

Weak entity

Attribute set

Question : What is the primary advantage of generalization in database design?

Increases redundancy

Complicates ER diagrams

Reduces data duplication and improves structure

Removes relationships

Question : Which of the following is a correct example of generalization?

Vehicle → Car, Bike

Person → Student, Faculty

Student, Faculty → Person

Employee → Manager

Question : Generalization in DBMS follows which type of approach?

Top-down

Hybrid

Bottom-up

Parallel

Question : Which of the following best describes generalization in DBMS?

Breaking a higher-level entity into lower-level entities

Combining lower-level entities into a higher-level entity based on common attributes

Creating relationships between unrelated entities

Eliminating entities from ER diagrams

Question : Which scenario best represents DBMS specialization?

Merging CUSTOMER and SUPPLIER into PERSON

Dividing PRODUCT into ELECTRONICS, BOOKS, and CLOTHES

onverting ER diagram to tables

Removing duplicate tuples

Question : Which step in specialization ensures data integrity by linking general and specialized entities?

Identifying common attributes

Creating specialized tables

Establishing relationships

Reducing redundancy

Question : Which of the following is NOT a characteristic of specialization?

Top-down approach

Reduces redundancy

Bottom-up technique

Divides entities into smaller parts

Question : In specialization, subclasses inherit attributes from:

Other subclasses

Relationship sets

Superclass

Weak entities

Question : Which of the following correctly describes specialization in DBMS?

Combining multiple entities into one higher-level entity

Breaking a higher-level entity into lower-level entities

Removing redundancy by normalization

Creating relations from ER diagrams

Question : Aggregation in DBMS is most useful when:

Data needs to be encrypted

Data needs to be summarized or analyzed

Data needs to be deleted

Data needs to be normalized

Question : Which of the following aggregate functions works with both numeric and non-numeric data?

SUM()

AVG()

COUNT()

MAX()

Question : Which SQL clause is specifically used to filter aggregated results?

WHERE

GROUP BY

HAVING

ORDER BY

Question : Which of the following best describes aggregation in an ER model?

Combining attributes into a composite key

Representing a relationship as an entity for another relationship

Splitting entities into multiple relations

Removing relationships from the schema

Question : In DBMS, aggregation is primarily used to:

Normalize data into multiple tables

Convert relationships into attributes

Treat a relationship as a higher-level entity

Eliminate redundancy completely

Question : Why are higher-degree relationships sometimes not preferred in implementation?

They are impossible to represent in ER diagrams

They increase redundancy

They are complex to convert into relational tables

They cannot store attributes

Question : In an n-ary relationship, the degree of the relationship is:

Number of attributes in the entity

Number of relationships in schema

Number of participating entity types

Number of tuples in table

Question : Which statement is TRUE about higher-degree relationships?

They are always decomposed into binary relationships without loss of information

They simplify modeling when multiple entities are interdependent

They cannot represent real-world scenarios

They are more common than binary relationships

Question : A relationship involving entities Teacher, Course, and Class is an example of:

Unary relationship

Binary relationship

Ternary relationship

Weak relationship

Question : Which of the following correctly defines a higher-degree (n-ary) relationship in DBMS?

Relationship involving exactly two entities

Relationship involving one entity only

Relationship involving three or more entities

Relationship involving only attributes

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