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Contents
▪ Database Management System (DBMS) - Definition and importance
▪ Introduction to Structured Query Language (SQL)

SQL: Structured Query Language
▪ SQL (Structured Query Language): Standard language for
interacting with relational databases
▪ Key characteristics:
▪ Declarative language
▪ Uses English-like syntax
▪ Supports data definition, manipulation, and control

SQL: Basics
▪ SQL Statements:
▪ Data Definition Language (DDL): CREATE, ALTER, DROP
▪ Data Manipulation Language (DML): SELECT, INSERT, UPDATE, DELETE
▪ Data Control Language (DCL): GRANT, REVOKE
▪ SQL Queries:
▪ SELECT statement: Retrieves data from a database table
▪ Example: SELECT * FROM Customers WHERE Country = 'USA';

SQL: SQL Database Operations
Creating Database and Tables:
• CREATE DATABASE database_name;
• CREATE TABLE table_name (column1 datatype, column2 datatype, ...);
Inserting Data:
• INSERT INTO table_name (column1, column2, ...) VALUES (value1,
value2, ...);
Updating Data:
• UPDATE table_name SET column_name = new_value WHERE
condition;
Deleting Data:
• DELETE FROM table_name WHERE condition;

SQL: SQL Database Operations
Joins:
Combine rows from multiple tables based on related columns
Types: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
Aggregation Functions:
Perform calculations on groups of rows
Examples: SUM, AVG, COUNT, MAX, MIN
Constraints:
Rules applied to columns to enforce data integrity
Examples: PRIMARY KEY, FOREIGN KEY, NOT NULL

Summary
• Database Management System (DBMS) is essential for efficient data
management.
• SQL is a powerful language for interacting with relational databases.
• Understanding DBMS and SQL enables effective data storage, retrieval, and
manipulation.

Day 2:
Entity Relationship Model

Precap
▪ Database Management System (DBMS) - Definition and importance
▪ Introduction to Structured Query Language (SQL)

Contents
▪ Entity Relationship Model
▪ Relationships
▪ ER Diagram Representations
▪ ER Diagram Examples

Entity Relationship Model
• An Entity Relationship Diagram (ERD) is a visual
representation of different data using conventions that
describe how these data are related to each other.
For example, the elements writer, novel, and consumer may be
described using ER diagrams this way:
•
The elements inside rectangles are
called entities while the items inside
diamonds denote the relationships
between entities.

Entity
• An entity can be a real-world object, either animate or inanimate,
that can be easily identifiable.
– For example, in a school database, students, teachers,
classes, and courses offered can be considered as entities.
– All these entities have some attributes or properties that give
them their identity.
An entity set is a collection of similar types of entities.
– An entity set may contain entities with attribute sharing
similar values.
– For example,
– a Students set may contain all the students of a school;
– likewise a Teachers set may contain all the teachers of a
school from all faculties. Entity sets need not be disjoint.
•

Weak Entity
• A weak entity is an entity that depends on the existence of
another entity.
In more technical terms it can defined as an entity that cannot be
identified by its own attributes.
It uses a foreign key combined with its attributed to form the
primary key.
An entity like order item is a good example for this.
– The order item will be meaningless without an order so it
depends on the existence of order.
•
•
•

Attributes
• Entities are represented by means of their properties,
called attributes.
• All attributes have values.
• For example, a student entity may have name, class,
and age as attributes.
• There exists a domain or range of values that can be
assigned to attributes.
• For example, a student's name cannot be a numeric
value. It has to be alphabetic. A student's age cannot
be negative, etc.

Types of Attributes
• Simple attribute − Simple attributes are atomic values, which
cannot be divided further. For example, a student's phone
number is an atomic value of 10 digits.
• Composite attribute − Composite attributes are made of more
than one simple attribute. For example, a student's complete
name may have first_name and last_name.

Types of Attributes (contd.,)
• Derived attribute − Derived attributes are the attributes that do not exist in
the physical database, but their values are derived from other attributes
present in the database.
• For example, average_salary in a department should not be saved directly in
the database, instead it can be derived.
•
•
For another example, age can be derived from data_of_birth.
For example for a circle the area can be derived from the radius.

Types of Attributes (contd.,)
• Single-value attribute − Single-value attributes contain single
value. For example − Social_Security_Number.
• Multi-value attribute − Multi-value attributes may contain more
than one values. For example, a person can have more than one
phone number, email_address, etc.
• For example a teacher entity can have multiple subject values.

• These attribute types can come together in a
way like −
• simple single-valued attributes
• simple multi-valued attributes
• composite single-valued attributes
• composite multi-valued attributes

Entity-Set and Keys
• Key is an attribute or collection of attributes that uniquely
identifies an entity among entity set.
For example, the roll_number of a student makes him/her
identifiable among students.
Super Key − A set of attributes (one or more) that collectively
identifies an entity in an entity set.
•
•
• Candidate Key − A minimal super key is called a candidate key.
An entity set may have more than one candidate key.
• Primary Key − A primary key is one of the candidate keys chosen
by the database designer to uniquely identify the entity set.

Relationship
•
•
The association among entities is called a relationship.
For example, an employee works_at a department, a
student enrolls in a course.
• Here, Works_at and Enrolls are called relationships.
For example, the entity “carpenter” may be related to the entity
“table” by the relationship “builds” or “makes”. Relationships
are represented by diamond shapes and are labeled using verbs.
•

Degree of Relationship
• The number of participating entities in a
relationship defines the degree of the
relationship.
• Binary = degree 2
• Ternary = degree 3
• n-ary = degree

Mapping Cardinalities
• Cardinality defines the number of entities in one entity set, which
can be associated with the number of entities of other set via
relationship set.
• One-to-one − One entity from entity set A can be associated with
at most one entity of entity set B and vice versa.

• One-to-many − One entity from entity set A can be associated
with more than one entities of entity set B however an entity
from entity set B, can be associated with at most one entity.

• Many-to-one − More than one entities from entity set A can
be associated with at most one entity of entity set B, however
an entity from entity set B can be associated with more than
one entity from entity set A.

• Many-to-many − One entity from A can be associated with more than one
entity from B and vice versa.

ER Diagram Representation
• Let us now learn how the ER Model is represented by means of
an ER diagram.
Any object, for example, entities, attributes of an entity,
relationship sets, and attributes of relationship sets, can be
represented with the help of an ER diagram.
•

Entity
• Entities are
Rectangles
represent.
represented by means
are named with the entity
of rectangles.
set they

Attributes
• Attributes are the properties of entities. Attributes are
represented by means of ellipses.
Every ellipse represents one attribute and is directly
connected to its entity (rectangle).
•

• If the attributes are composite, they are further divided in a
tree like structure. Every node is then connected to its
attribute. That is, composite attributes are represented by
ellipses that are connected with an ellipse.

• Multivalued attributes are depicted by double
ellipse.

• Derived attributes are depicted by dashed ellipse.

Relationship
• Relationships are represented by diamond-shaped box.
Name of the relationship is written inside the diamond-box.
All theentities (rectangles) participating in a relationship,
are connected to it by a line.
•
•
• Binary Relationship and Cardinality
• A relationship where two entities are participating is called a binary
relationship. Cardinality is the number of instance of an entity from
a relation that can be associated with the relation.

• One-to-one − When only one instance of an entity is
associated with the relationship, it is marked as '1:1'. The
following image reflects that only one instance of each entity
should be associated with the relationship. It depicts one-to-
one relationship.

• One-to-many − When more than one instance of an entity is
associated with a relationship, it is marked as '1:N'. The
following image reflects that only one instance of entity on
the left and more than one instance of an entity on the right
can be associated with the relationship. It depicts one-to-
many relationship.

• Many-to-one − When more than one instance of entity is
associated with the relationship, it is marked as 'N:1'. The
following image reflects that more than one instance of an
entity on the left and only one instance of an entity on the right
can be associated with the relationship. It depicts many-to-one
relationship.

• Many-to-many − The following image reflects that more
than one instance of an entity on the left and more than one
instance of an entity on the right can be associated with the
relationship. It depicts many-to-many relationship.

• Participation Constraints
• Total Participation − Each entity is involved in the
relationship. Total participation is represented by double lines.
• Partial participation − Not all entities are involved in the
relationship. Partial participation is represented by single lines.

Generalization Aggregation
• The ER Model has the power of expressing database entities in a conceptual
hierarchical manner.
As the hierarchy goes up, it generalizes the view of entities, and as we go
deep in the hierarchy, it gives us the detail of every entity included.
•
• Going up in this structure is called generalization, where entities are
clubbed together to represent a more generalized view.
• For example, a particular student named Mira can be generalized along with
all the students.
• The entity shall be a student, and further, the student is a person. The
reverse is called specialization where a person is a student, and that student
is Mira.

Generalization
• The process of generalizing entities, where the generalized entities contain
the properties of all the generalized entities, is called generalization.
• In generalization, a number of entities are brought together into one
generalized entity based on their similar characteristics. For example,
pigeon, house sparrow, crow and dove can all be generalized as Birds.

Specialization
• Specialization is the opposite of generalization. In
specialization, a group of entities is divided into
sub-groups based on their characteristics.
•
• Take a group ‘Person’ for example. A person has
name, date of birth, gender, etc. These
properties are common in all persons, human
beings. But in a company, persons can be
identified as employee, employer, customer, or
vendor, based on what role they play in the
company.
Similarly, in a school database, persons can be
specialized as teacher, student, or a staff, based
on what role they play in school as entities.

Inheritance
• We use all the above features of ER-
Model in order to create classes of
objects in object-oriented
programming.
The details of entities are generally
hidden from the user; this process
known as abstraction.
Inheritance is an important feature of
Generalization and Specialization. It
allows lower-level entities to inherit the
attributes of higher-level entities.
For example, the attributes of a Person
class such as name, age, and gender can
be inherited by lower-level entities
such as Student or Teacher.
•
•
•

ER Diagram Example
• Suppose you are given the following requirements for a simple database for the
National Hockey League (NHL):
•
•
•
•
the NHL has many teams,
each team has a name, a city, a coach, a captain, and a set of players,
each player belongs to only one team,
each player has a name, a position (such as left wing or goalie), a skill level,
and a set of injury records,
•
•
a team captain is also a player,
a game is played between two teams (referred to as host_team and guest_team)
and has a date (such as May 11th, 1999) and a score (such as 4 to 2).
• Construct a clean and concise ER diagram for the NHL database.

• Question 2:
• A university registrar’s office maintains data about the following
entities:
• courses, including number, title, credits, syllabus, and
prerequisites;
• course offerings, including course number, year, semester, section
number, instructor(s), timings, and classroom;
• students, including student-id, name, and program;
• instructors, including identi-cation number, name, department,
and title.
• Further, the enrollment of students in courses and grades
awarded to students in each course they are enrolled for must be
appropriately modeled. Construct an E-R diagram for the
registrar’s of-ce.Document all assumptions that you make about
the mapping constraints.

• Question 3:
(a)Construct an E-R diagram for a car-insurance
company whose customers own one or more cars
each. Each car has associated with it zero to any
number of recorded accidents.
(b)Construct appropriate tables for the above ER
Diagram ?

Car insurance tables:
•person (driver-id, name, address)
•car (license, year,model)
•accident (report-number, date, location)
•participated(driver-id, license, report-number,
damage-amount)

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