Easy2Siksha Sample Paper
(GNDU) MOST REPETED (IMPORTANT) QUESTIONS
BCA 3rd SEMESTER
Database Management System
Repeated Quesons
1. Database Management System (DBMS): Concept, Advantages over Tradional File
Systems
• Frequency: 2 mes
• Years Appeared: 2021, 2022
2. Enty–Relaonship (E-R) Model / E-R Diagram Concepts (Strong Enty, Weak Enty,
Relaonships, Specializaon, Generalizaon)
• Frequency: 3 mes
• Years Appeared: 2022, 2023, 2024
2025 Smart Predicon Table
Based on 4-Year Queson Paper Analysis
Queson Topic
Repeats
Years Appeared
Priority Level
Normalizaon (BCNF, 3NF, 4NF, MVD)
4
2021, 2022, 2023, 2024
Very High
E-R Model / Diagram Concepts
3
2022, 2023, 2024
High
Easy2Siksha Sample Paper
(GNDU) MOST REPETED (IMPORTANT) Answer
BCA 3rd SEMESTER
Database Management System
Solved Answer
1. Database Management System (DBMS): Concept, Advantages over Tradional File
Systems
• Frequency: 2 mes
• Years Appeared: 2021, 2022
Ans: A Fresh Beginning: The Tale of Two Towns
Once upon a time, there were two towns — Fileville and Dataville.
• In Fileville, every shopkeeper kept their own ledger books. If you wanted to know
how many apples were sold last month, you had to run from shop to shop, flip
through dusty pages, and hope the handwriting was clear. Sometimes, two shops
had different numbers for the same thing. Mistakes were common, and finding
information took forever.
• In Dataville, the townsfolk had built a central library with a smart librarian. All
shopkeepers sent their sales records to this library. The librarian stored everything in
an organized way, could answer any question instantly, and made sure there were
no duplicate or conflicting records.
Fileville is like the traditional file system. Dataville is like a Database Management System
(DBMS).
Part 1: Concept of DBMS
Definition: A Database Management System is software that allows users to create, store,
organize, retrieve, update, and manage data in a structured way. It acts as an interface
between the user (or application) and the database.
Key Roles of a DBMS
1. Data Storage – Organizes data in tables, rows, and columns.
2. Data Retrieval – Lets you query data using languages like SQL.
3. Data Manipulation – Insert, update, delete records easily.
4. Data Security – Controls who can access or modify data.
5. Data Integrity – Ensures accuracy and consistency.
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Diagram – DBMS in Action
Part 2: Traditional File System – How It Works
In a traditional file system:
• Data is stored in separate files (text, CSV, binary).
• Each application manages its own files.
• No central control — each program decides how to store and retrieve data.
Problems with File Systems
1. Data Redundancy – Same data stored in multiple files.
2. Inconsistency – Updates in one file may not be reflected in others.
3. Difficulty in Access – Complex code needed to retrieve specific data.
4. Poor Security – Hard to control who can access what.
5. No Concurrent Access Control – Multiple users editing at once can corrupt data.
6. Scalability Issues – Hard to manage large volumes of data.
Diagram – Traditional File System
Program A --> File A
Program B --> File B
Program C --> File C
(No central control, data scattered)
Part 3: How DBMS Solves These Problems
Let’s revisit Dataville — the DBMS town.
1. Centralized Storage – All data is stored in one place.
2. Controlled Access – The librarian (DBMS) checks permissions before giving data.
3. Consistency – Any update is reflected everywhere instantly.
4. Easy Queries – You can ask complex questions without reading every file.
5. Concurrent Access – Multiple users can work at the same time without conflicts.
Part 4: Advantages of DBMS over Traditional File Systems
Let’s break them down clearly.
1. Reduced Data Redundancy
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• File System: Same customer’s address stored in multiple files.
• DBMS: Data stored once in a table; referenced wherever needed.
2. Improved Data Consistency
• File System: One file says “Ravi Kumar,” another says “Ravi K.”
• DBMS: Single source of truth; updates are global.
3. Better Data Security
• File System: Anyone with file access can read/modify data.
• DBMS: Role-based access control; encryption possible.
4. Easier Data Access
• File System: Need custom programs to search.
• DBMS: Use SQL queries like:
sql
SELECT * FROM Customers WHERE City='Amritsar';
5. Support for Concurrent Access
• File System: Risk of overwriting each other’s changes.
• DBMS: Transaction management ensures safe multi-user access.
6. Backup and Recovery
• File System: Manual backups; recovery is hard.
• DBMS: Automated backups and recovery tools.
7. Data Integrity
• File System: No built-in rules.
• DBMS: Constraints (PRIMARY KEY, FOREIGN KEY) enforce rules.
8. Scalability
• File System: Becomes slow and unmanageable with large data.
• DBMS: Designed to handle millions of records efficiently.
Comparison Table – DBMS vs File System
Feature
File System
DBMS
Data Redundancy
High
Low
Consistency
Low
High
Security
Basic
Advanced
Easy2Siksha Sample Paper
Access
Complex
Easy (SQL)
Concurrency
Poor
Excellent
Backup/Recovery
Manual
Automated
Integrity Rules
Not enforced
Enforced
Scalability
Limited
High
Part 5: Real-Life Example
Imagine a university:
• File System: Admissions, exams, and hostel departments each keep their own
student files. Updating a student’s phone number means changing it in three places.
• DBMS: One central student database. Update once, and all departments see the
change instantly.
Part 6: DBMS Architecture (Simplified)
Final Story Recap
In the world of data towns:
• Fileville is messy, slow, and error-prone.
• Dataville is organized, secure, and efficient — thanks to its smart librarian, the
DBMS.
• Moving from a traditional file system to a DBMS is like upgrading from scattered
notebooks to a central, intelligent library.
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2. Enty–Relaonship (E-R) Model / E-R Diagram Concepts (Strong Enty, Weak Enty,
Relaonships, Specializaon, Generalizaon)
• Frequency: 3 mes
• Years Appeared: 2022, 2023, 2024
Ans: A Fresh Beginning: The City Planner’s Blueprint
Imagine you are the chief city planner of a brand-new smart city. Before a single brick is
laid, you need a blueprint that shows:
• What kinds of buildings will exist (houses, offices, schools)
• How they are connected (roads, utilities)
• Special categories (luxury houses vs. regular houses)
• General rules (all buildings have an address)
This blueprint is exactly what the Entity–Relationship (E-R) Model is for a database. It’s a
visual plan that shows the entities (things we store data about), their attributes
(properties), and the relationships between them.
Part 1: Concept of E-R Model
Definition: The Entity–Relationship Model is a high-level conceptual data model that
describes the structure of a database in terms of:
• Entities – real-world objects or concepts
• Attributes – properties of those entities
• Relationships – associations between entities
It’s usually represented as an E-R Diagram — a visual map of the database.
Why it’s important:
• Helps in database design before implementation.
• Makes communication between developers, clients, and database designers easier.
• Reduces errors by clarifying structure early.
Basic E-R Diagram Symbols:
Symbol
Meaning
Rectangle
Entity
Ellipse
Attribute
Diamond
Relationship
Double Rectangle
Weak Entity
Double Ellipse
Multivalued Attribute
Underlined Attribute
Primary Key
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Part 2: Strong Entity
Concept
A Strong Entity is an entity that can be uniquely identified by its own attributes, without
depending on any other entity.
Analogy: In our city, a House has its own unique house number — it doesn’t need to be
identified by another building.
Example:
• Entity: Student
• Primary Key: Roll Number
• Attributes: Name, Age, Course
Diagram – Strong Entity
Part 3: Weak Entity
Concept
A Weak Entity cannot be uniquely identified by its own attributes alone. It depends on a
Strong Entity (called its owner) and a partial key.
Analogy: In our city, a Room in a house doesn’t have a unique identity unless you know
which house it belongs to.
Example:
• Entity: Dependent
• Owner Entity: Employee
• Partial Key: Dependent Name
• Attributes: Age, Relationship
Diagram – Weak Entity
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Key Points:
• Represented by double rectangle in E-R diagram.
• Identifying relationship shown with double diamond.
Part 4: Relationships
Concept
A Relationship is an association between two or more entities.
Analogy: In our city, a Road connects two buildings — that’s a relationship.
Types of Relationships
1. One-to-One (1:1) Example: Each person has one passport.
2. One-to-Many (1:N) Example: One teacher teaches many students.
3. Many-to-Many (M:N) Example: Students enroll in many courses; each course has
many students.
Diagram – Relationship Example
STUDENT --------(Enrolls)-------- COURSE
Attributes of Relationships:
• Sometimes relationships have their own attributes. Example: In “Enrolls,” the
attribute could be Date of Enrollment.
Part 5: Specialization
Concept
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Specialization is the process of defining subclasses of an entity that have their own specific
attributes.
Analogy: In our city, “Vehicle” is a general category, but we can have Car and Bike as special
types, each with unique features.
Example:
• Entity: Employee
• Specialized Entities: Manager, Engineer
• Manager has attribute: Department Managed
• Engineer has attribute: Project Assigned
Diagram – Specialization
Key Points:
• Top-down approach.
• In E-R diagrams, shown with a triangle pointing to subclasses.
Part 6: Generalization
Concept
Generalization is the reverse of specialization — combining two or more entities into a
higher-level entity based on common attributes.
Analogy: In our city, “Car” and “Bike” can be generalized into “Vehicle” because both have
common attributes like registration number and owner.
Example:
• Entities: Undergraduate Student, Postgraduate Student
• Generalized Entity: Student
Diagram – Generalization
Easy2Siksha Sample Paper
Key Points:
• Bottom-up approach.
• Useful for reducing redundancy.
Part 7: Complete E-R Diagram Example
Let’s design a mini-university database:
Entities:
• Student (Strong)
• Course (Strong)
• Enrollment (Relationship)
• Dependent (Weak, owned by Student)
Specialization:
• Student → UG_Student, PG_Student
Generalization:
• UG_Student and PG_Student → Student
Diagram (Text Representation)
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Part 8: Why E-R Model is Loved in Design
• Clarity: Visual representation makes it easy to understand.
• Communication: Bridges gap between technical and non-technical stakeholders.
• Foundation: Serves as blueprint for relational schema.
• Error Reduction: Identifies missing entities or relationships early.
Part 9: Real-Life Example Story
Imagine designing a hospital database:
• Strong Entities: Doctor, Patient
• Weak Entity: Prescription (depends on Patient)
• Relationships: Doctor “treats” Patient
• Specialization: Doctor → Surgeon, Physician
• Generalization: Inpatient and Outpatient → Patient
By drawing the E-R diagram first, you ensure no important detail is missed before coding.
Final Story Recap
In the city of data:
• Strong Entities are independent buildings with their own address.
• Weak Entities are rooms that need a building to be identified.
• Relationships are the roads connecting them.
• Specialization is creating luxury or specialized versions of buildings.
• Generalization is grouping similar buildings into one category.
The E-R Model is your city blueprint
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