UNIT 1 INTRODUCTION TO DBMS, ER DIAGRAM, RELATION

Unit-I Part B
Entity Relationship Model
Prof. Bhakti B Pawar
Assistant Professor

Department of Information Technology, Sanjivani COE
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What is Data Model?
•A data model is a collection of conceptual tools for describing data,
data relationships, data semantics, and consistency constraints.
•Data model used to describe the database system at the
requirements collection stage
• high level description.
• easy to understand for the enterprise managers.
• rigorous enough to be used for system building.

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Data Model
• The entity–relationship (E-R) model
• is a high-level data model.
• It consists of a collection of basic objects, called entities, and of relationships
among these objects.
• The relational model
• is a lower-level model.
• It uses a collection of tables to represent both data and the relationships among
those data.
• Due to its conceptual simplicity, majority of database products are based on the
relational model.
• Designers often formulate database schema design by first modeling data at a
high level, using the E-R model, and then translating it into the relational model.

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E-R Model
• Stands for an Entity-Relationship model
• High-level data model: Used to define the data elements and relationship for a
specified system.
• Widely used conceptual level Data Model
• It develops a conceptual design for the database.
• It also develops a very simple and easy to design view of data.
• In ER modeling, the database structure is portrayed as a diagram called an
entity-relationship diagram.
• Concepts available in the model
• Entities
• Attributes of entities.
• Relationships between entities.
• The ER model also has an associated diagrammatic representation, the ER diagram, which can
express the overall logical structure of a database graphically.

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Entity
• Entity - a thing of independent physical or conceptual existence and distinguishable.
• In the University database context, an individual student, faculty member, a class room, a
course are entities.
• Entity Set or Entity Type:
• It is a set of entities of the same type that share the same properties, or attributes.
• Student entity set – collection of all student entities.
• Course entity set – collection of all course entities.
• An entity is represented by a set of attributes:
• Descriptive properties possessed by all members of an entity set.
• Example:
• instructor = (ID, name, salary )
• course= (course_id, title, credits)
• Each entity has a value for each of its attributes.

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Attribute
• Each entity is described by a set of attributes/properties that have
associated values and information
• student entity
• StudName – name of the student.
• RollNumber – the roll number of the student.
• Mobile – Mobile nos of the student etc.
• All entities in an Entity set/type have the same set of attributes.
• For each attribute, there is a set of permitted values, called the domain,
or value set, of that attribute.
• The domain of attribute
• customer-name might be the set of all text strings of a certain length.
• loan-number might be the set of all strings of the form “L-n” where n is a
positive integer

Database
• A database thus includes a collection of entity sets, each of which contains any number of
entities of the same type.
• Figure shows part of a bank database that consists of two entity sets: customer and loan
• An attribute of an entity set is a function that maps from the entity set into a domain.
• An entity set may have several attributes,
• Each entity can be described by a set of (attribute, data value) pairs, one pair for each
attribute of the entity set.
• For example, a particular customer entity may be described by the set
{(customer-id, 677- 89-9011), (customer-name, Hayes), (customer-street, Main)}
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Types of Attributes (1/2)
• Simple Attributes: having atomic or indivisible values.
Example:
• Dept_Name– a string
• PhoneNumber– a ten digit number
• Composite Attributes:
• having several components in the value.
• divided attributes into subparts (other attributes).
• a composite attribute may appear as a hierarchy (Address)
Example:
• Qualification with components- (DegreeName, Year, UniversityName)
• Land_line_no: (stdcode,areano,actualno)
• Address:
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• Derived Attributes: Attribute value is dependent on some other
attribute.
Example:
• Age depends on DateofBirth: So age is a derived attribute.
• Interest amount: Based on Loan Amount
• Null Value:
• An attribute takes a null value when an entity does not have a value for it.
• Example: Middle Name
• Null can also designate that an attribute value is unknown.
• An unknown value may be either missing (the value does exist, but we do not
have that information)
• not known (we do not know whether or not the value actually exists).

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• Single-valued:
• having only one value rather than a set of values.
• for instance,
• PlaceOfBirth – single string value.
• Multi-valued:
• having a set of values rather than a single value.
• for instance:
• CoursesEnrolled attribute for student (all courses in semester)
• EmailAddress attribute for student (personal email, official email)
• PreviousDegree attribute for student.
• Attributes can be:
• Simple single-valued
• Simple multi-valued
• Composite single-valued
• Composite multi-valued.

Notations for Entities
•Entity: Rectangle
•Attributes: Ellipse connected to Rectangle
• Multivalued Attributes: Double Ellipse
• Composite Attributes:
• Ellipse Connected to ellipse
• Derived Attributes: Dashed Ellipse
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Domains of Attributes
•Each attribute takes values from a set called its domain
• For instance, studentAge – {17,18, …, 55}
• HomeAddress – character strings of length 35
•Domain of composite attributes:
• cross product of domains of component attributes
•Domain of multi-valued attributes:
• set of subsets of values from the basic domain

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Entity Sets and Key Attributes
• Key: an attribute or a collection of attributes whose value(s) uniquely
identify an entity in the entity set.
• Example:
• RollNumber - Key for Student entity set
• EmpID - Key for Faculty entity set
• HostelName, RoomNo - Key for Student entity set
• A key for an entity set may have more than one attribute.
• An entity set may have more than one key.
• Keys can be determined only from the meaning of the attributes in the
entity type.
• Determined by the designers

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Relationship Sets
•A relationship is an association among several entities.
• For example, we can define a relationship that associates customer Hayes
with loan L-15.
• This relationship specifies that Hayes is a customer with loan number
L-15.
•A relationship set is a set of relationships of the same type.
•Formally, it is a mathematical relation on n ≥ 2 (possibly
nondistinct) entity sets.
If E1, E2,...,En are entity sets, then a relationship set R is a subset of
where (e1, e2,...,en) is a relationship.
{(e1, e2,...,en) | e1 ∈ E1, e2 ∈ E2,...,en ∈ En

Relationship Sets
• We define the
• relationship set borrower to denote the association between customers and the bank loans that the
customers have
• loan-branch to denote the association between a bank loan and the branch in which that loan is
maintained.
• The association between entity sets is referred to as participation; that is, the entity sets
E1, E2,...,En participate in relationship set R.
• A relationship instance in an E-R schema represents an association between the named
entities in the real-world enterprise that is being modeled
• Example:
• The individual customer entity Hayes, who has customer identifier 677-89-9011, and the loan entity
L-15 participate in a relationship instance of borrower.
• A relationship may also have attributes called descriptive attributes
• Entity sets student and course which participate in a relationship set registered-for
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Relationships (1/2)
•When two or more entities are associated with each other, we
have an instance of a Relationship.
• E.g.: student Ramesh enrolls in Discrete Mathematics course
•Relationship enrolls has Student and Course as the participating
entity sets.
• Formally, enrolls ⊆ Student × Course
• (s,c) ∈ enrolls ⇔ Student ‘s’ has enrolled in Course ‘c’
• Tuples in enrolls – relationship instances
• enrolls is called a relationship Type/Set

Relationships (2/2)
•Relationship: diamond shaped box
• Rectangle of each participating entity is connected by a line to this
diamond.
• Name of the relationship is written in the box.
•Degree of Relationship: the number of participating entities.
• Degree 2: binary : one that involves two entity sets.
• Degree 3: ternary:
• The relationship set works-on among employee, branch, and job is an example of a
ternary relationship.
• Degree n: n-ary
• Binary relationships are very common and widely used.
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Constraints: Cardinality Ratios
• Mapping cardinalities or Cardinality Ratios: Express the number of entities to which another
entity can be associated via a relationship set.
• For a binary relationship set the mapping cardinality must be one of the following types:
• One-to-one:
• An E1 entity may be associated with at most one E2 entity and
• similarly an E2 entity may be associated with at most one E1 entity.
• One-to-many:
• An E1 entity may be associated with many E2 entities whereas
• an E2 entity may be associated with at most one E1 entity.
• Many-to-one:
• An E2 entity may be associated with many E1 entities whereas
• an E1 entity may be associated with at most one E2 entity.
• Many-to-many:
• Many E1 entities may be associated with a single E2 entity and
• a single E1 entity may be associated with many E2 entities.

Mapping Cardinalities
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Representing Cardinality Constraints in ER Diagram
•We express cardinality constraints by drawing either
• a directed line (->), signifying “one,”
• an undirected line (—), signifying “many,”
between the relationship set and the entity set.
•One-to-one relationship between an instructor and a student :
• A student is associated with at most one instructor via the relationship
advisor
• A student is associated with at most one department via stud_dept
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One-to-Many Relationship
•One-to-Many relationship between an instructor and a student
• an instructor is associated with several (including 0) students via advisor
• a student is associated with at most one instructor via advisor
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Many-to-One Relationships
•Many-to-One relationship between an instructor and a student
• An instructor is associated with at most one student via advisor,
• A student is associated with several (including 0) instructors via adviso
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Many-to-Many Relationships
•Many-to-Many relationship between an instructor and a student
• An instructor is associated with several (possibly 0) students via advisor
• A student is associated with several (possibly 0) instructors via advisor
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Reflection Quiz!!
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Constraints: Participation Constraints (1/2)
•An entity set may participate in relation either totally or partially
•Total participation (indicated by double line):
• The participation of an entity set E in a relationship set R is said to be total
if every entity in E participates in at least one relationship in R.
• Participate in some association in tuple or relationship
•Partial participation:
• If only some entities in E participate in relationships in R, the
participation of entity set E in relationship R is said to be partial
• Not all entities involved in association or tuple of relationship
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Participation Constraints (1/2)
•Participation of instructor in advisor is partial
•Participation of student in advisor relation is total
• Every student must have an associated instructor
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Keys
•Conceptually, individual entities are distinct
•A key allows us to identify a set of attributes that suffice to
distinguish entities from each other.
•Keys also help uniquely identify relationships, and thus
distinguish relationships from each other.

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Key: Super Key
•A super key :is a set of one or more attributes that collectively,
allow to identify uniquely an entity in the entity set.
•For example,
• the customer-id attribute of the entity set customer is sufficient to
distinguish one customer entity from another. Thus, customer-id is a
superkey.
• Similarly, the combination of customer-name and customer-id is a
superkey for the entity set customer.
• The customer-name attribute of customer is not a superkey, because
several people might have the same name
•The concept of a super key is not sufficient:
• a super key may contain extraneous attributes.

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Key: Candidate Key
• Super keys for which no proper subset is a super key. Such minimal
super keys are called candidate keys.
• It is possible that several distinct sets of attributes could serve as a
candidate key.
• Suppose that a combination of customer-name and customer-street is sufficient
to distinguish among members of the customer entity set.
• Then, both {customer-id} and {customer-name, customer-street} are candidate
keys.
• Although the attributes customer_id and customer-name together can
distinguish customer entities, their combination does not form a
candidate key, since the attribute customer-id alone is a candidate key.

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Keys
•Use the term primary key to denote a candidate key that is chosen
by the database designer for identifying entities within an entity
set.
•A key (primary, candidate, and super) is a property of the entity
set, rather than of the individual entities.
•Any two individual entities in the set are prohibited from having
the same value on the key attributes at the same time.

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Entity-Relationship Diagram
• Rectangles: which represent entity sets
• Ellipses: which represent attributes
• Diamonds: which represent relationship sets
• Lines: which link attributes to entity sets and entity sets to relationship
sets
• Double ellipses: which represent multivalued attributes
• Dashed ellipses: which denote derived attributes
• Double lines: which indicate total participation of an entity in a
relationship set
• Double rectangles: which represent weak entity sets

• The relationship set borrower may be many-to-many, one-to-many,
many-to-one, or one-to-one.
• An undirected line from the relationship set borrower to the entity set loan specifies that
borrower is either a many-to-many or one-to-many relationship set from customer to
loan
• A directed line from the relationship set borrower to the entity set loan specifies that
borrower is either a one-to-one or many-to-one relationship set,
• from customer to loan; borrower cannot be a many-to-many or a one-to-many relationship set from
customer to loan.
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•If a relationship set has also some attributes associated with it,
then we link these attributes to that relationship set.
•E-R diagram with an attribute attached to a relationship set
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Exercise
• Draw the diagram for customer
• A composite attribute name, with component attributes first-name, middle-initial, and last-name replaces the
simple attribute customer-name of customer.
• A composite attribute address, whose component attributes are street, city, state, and zip-code replaces the
attributes customer-street and customer-city of customer.
• The attribute street is itself a composite attribute whose component attributes are street-number, street-name,
and apartment number.
• Multivalued attribute phone-number, Derived attribute age,
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Roles:
•Indicate roles in E-R diagrams by labeling the lines that connect
diamonds to rectangles.
•Example:
• role indicators manager and worker between the employee entity set and
the works-for relationship set.
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Ternary Relationship
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Structural Constraints
• Cardinality Ratio and Participation Constraints are together called
Structural Constraints.
• They are called constraints as the data must satisfy them to be
consistent with the requirements.
• Min-Max notation: pair of numbers (m,n) placed on the line connecting an entity
to the relationship.
• m: the minimum number of times a particular entity must appear in the
relationship tuples at any point of time
• 0 – partial participation
• ≥ 1 – total participation
• n: similarly, the maximum number of times a particular entity can appear in the
relationship tuples at any point of time

Let’s Check understanding
•Draw a diagram for Library Management system
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Bank Database
e.
• Bank have Customer.
• Banks are identified by a name, code, address of main
office.
• Banks have branches.
• Branches are identified by a branch_no., branch_name,
address.
• Customers are identified by name, cust-id, phone number,
address.
• Customer can have one or more accounts.
• Accounts are identified by account_no., acc_type, balanc
• Customer can avail loans.
• Loans are identified by loan_id, loan_type and amount.
• Account and loans are related to bank’s branch.
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Extended E-R Features
Specialization
Generalization

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Specialization
•An entity set may include subgroupings of entities that are distinct
in some way from other entities in the set.
• For instance, a subset of entities within an entity set may have attributes
that are not shared by all the entities in the entity set.
• The E-R model provides a means for representing these distinctive entity
groupings.
• An entity set person {name, street, and city} further classified as customer
employe
•The process of designating subgroupings within an entity set is
called specialization.
• The specialization of person allows us to distinguish among persons
according to whether they are employees or customers.

Specialization
• Specialization is depicted by a triangle component
labeled ISA ,stands for is-a
• a customer “is a” person.
• The ISA relationship may also be referred to as a
superclass-subclass relationship.
• Higher and lower-level entity sets are depicted as regular
entity set: rectangles containing the name of the entity set.
• Example:
• bank employees
• Officer
• Teller
• secretary
• Account:
• attributes account-number and balance.
• savings-account and checking-account.
• savings-account: All the attributes of account and interest-rate.
• Checkingaccount: all the attributes of account, overdraftamount.
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Generalization
• There are similarities between the customer entity set and the
employee entity set in the sense that they have several attributes in
common.
• This commonality can be expressed by generalization, which is a containment
relationship that exists between a higher-level entity set and one or more
lower-level entity sets.
• Person is the higher-level entity set and customer and employee are lower-level
entity sets.
• Higher- and lower-level entity sets also may be designated by the terms
superclass and subclass, respectively.
• The person entity set is the superclass of the customer and employee
subclasses.
• Generalization is a simple inversion of specialization

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Constraint
•A higher-level entity set with attributes and relationships that
apply to all of its lower-level entity sets
•Lower-level entity sets with distinctive features that apply only
within a particular lower-level entity set
•Constraint
• Condition defined-userdefined
• Disjoint- Overlapping
• Total - Partial

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Constraint
• Condition-defined: Lower-level entity sets, membership is evaluated on
the basis of whether or not an entity satisfies an explicit condition or
predicate.
• Account has the attribute account-type
• All account entities are evaluated on the defining account-type attribute.
• Only those entities that satisfy the condition account-type = “savings account” are allowed
to belong to the lower-level entity set person.
• All entities that satisfy the condition account-type = “checking account” are included in
checking account.
• Since all the lower-level entities are evaluated on the basis of the same attribute this type of
generalization is said to be attribute-defined.
• User-defined: Lower-level entity sets are not constrained by a
membership condition; rather, the database user assigns entities to a
given entity set

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Constraint
• Constraint relates to whether or not entities may belong to more than one
lower-level entity set within a single generalization.
• Disjoint: A disjointness constraint requires that an entity belong to no more
than one lower-level entity set.
• Example: an account entity can satisfy only one condition for the account-type attribute
either a savings account or a checking account, but cannot be both.
• Overlapping: The same entity may belong to more than one lower-level entity
set within a single generalization.
• Example: Consider the employee work team example, and assume that certain
managers participate in more than one work team.
A given employee may therefore appear in more than one of the team entity sets that
are lower-level entity sets of employee.
• Example: Generalization applied to entity sets customer and employee leads to a
higher-level entity set person.
The generalization is overlapping if an employee can also be a customer.

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Completeness constraint
• Completeness constraint on a generalization or specialization:
• specifies whether or not an entity in the higher-level entity set must belong to at
least one of the lower-level entity sets within the generalization/specialization.
• Total generalization or specialization:
• Each higher-level entity must belong to a lower-level entity set
• Shown by using a double line to connect the box representing the higher-level
entity set to the triangle symbol
• The account generalization is total: All account entities must be either a savings
account or a checking account.
• Partial generalization or specialization:
• Some higher-level entities may not belong to any lower-level entity set.
• Partial generalization is the default.

UNIT 1 INTRODUCTION TO DBMS, ER DIAGRAM, RELATION

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