Indira Gandhi

National Open University

presents

A Video Lecture

Course:Systems Analysis

DATA MODELING

MODEL

A Model is an abstraction of something for the purpose of understanding it before building it.

DATA MODELING

• Answers a set of following specific questions that are relevant to any data processing application

Questions answered by a Data Model

• What are the primary data objects to be processed by the system

• What is the composition of each data object and what attributes describe the object

• Where do objects currently reside

• What are the relationships between each object and other objects

• What is the relationship between the objects and the processes that transform them

Questions answered by a Data Model

• To answer those questions,Data modeling makes use of Entity-Relationship Diagram(ERD)

• ERD enables a Software Engineer to identify data objects and their relationships using a graphical notation

DATA OBJECTS

A data object is a representation of almost any composite information that must be understood by software.By composite information,we mean something that has a number of different properties or attributes.

A person is a data object

A car is a data object

KeyOne or more attributes which uniquely identify a data object

Attributes of Person: Name,Address,Age, Driving license number

Driving license number is the key

Attributes of Car: Make,Model,Chassis Number, Body type,Color

Chassis Number is the key

RELATIONSHIPS

Data objects are connected to one another in a variety of different ways

Here, owns is the relationship

Example: a Person owns a Car

Identification of Objects, Attributes & Relationships

Problem:

A University should schedule its class rooms for final Exams. Examinations will be conducted for all courses for students of all sections

• Course

• Section

• Room

Data Objects

• Name

• Department

• Code

Attributes of Course

• S-number

• Enrollment

Attributes of Section

• R-number

• Capacity

• Building

Attributes of Room

Relationships:

• Code & S-number

Entity Relationship Model

Simple and Composite Attributes

• CITY is a Simple attribute

• NAME is a Composite attribute because we can subdivide it into First Name,Middle Name and Last Name

Single and Multi Valued Attributes

• AGE is a single valued attribute

• DEPENDENT-NAME is a multi valued attribute

Derived Attributes

• EMPLOYEMENT-LENGTH of Employee entity set is a derived attribute of Start-date and Current-date

Keys

•Super Key

•Candidate Key

For example,Consider CUSTOMER entity set with attributes (1)Social security (2)Customer name (3)Customer street (4)Customer city

Now,Social security is a super key.Also,any set of attributes containing Social security forms a super key

So,Social-security is also candidate key

ENTITY-RELATIONSHIP DIAGRAMA E-R diagram consists of following components:

• Rectangles-represent Entity sets

• Ellipses-represent Attributes

• Diamonds-represent Relationship sets

• Lines-link attributes to Entity sets and Entity sets to relationship sets

• Double Ellipses-represent multi valued attributes

• Dashed Ellipses-denote derived attributes

• Double lines-indicate total participation of an entity in a relationship set

E-R diagram corresponding to Customers and Loans

RELATIONSHIPS BETWEEN ENTITY SETS

• One to Many

• Many to One

• One to One

RELATIONSHIP SETSSo,Attributes of Borrower :Social Security, Loan-number

WEAK ENTITY SETS

For example, an entity set with attributes Name,Age,Height is a Weak Entity Set

STRONG ENTITY SET

• An Entity set with Passport no.,Name ,age,Height,Address is a Strong Entity Set as Passport no. can be used as key attribute

Summary

• Definition of Modeling

• Questions answered by Data Modeling

• Definitions of Data Object,Attributes and Relationships

Summary(contd.)

• Analyzing a given problem and finding Data Objects, Attributes and Relationships between objects of that problem

• Introduction to Entity – Relationship Modelling

Summary(Contd.)

• Simple and Composite Attributes

• Single and Multivalued Attributes

• Derived Attributes

• Candidate Keys

• Entity-Relationship Diagram

Summary(contd.)

• Weak Entity Sets

• Strong Entity Sets