Fundamentals of Data Modeling and Database Design by Dr. Kamal Gulati

Data
Models
Dr. Kamal Gulati
Fundamentals of Data Modeling and Database Design

Dr. Kamal Gulati
ERM vs. ERD
• ERM (Entity Relationship Data Model / Entity–
Relationship Modeling): is a detailed, Logical
representation of the data for an organization or for
a business area. ERM is expressed in terms of :
• Entities
• Attributes
• Relationships
• ERD (Entity Relationship Diagram): is a graphical
representation of a Entity-Relationship Model.

Dr. Kamal Gulati
ERM (Entity Relationship
Modeling)
• Is a data model for describing the data or
information aspects of a business domain or its
process requirements, in an abstract way that lends
itself to ultimately being implemented in a
database such as a relational database.
• Data Model: A set of concepts to describe the structure
of a database and certain constrain that the database
shouldobey.

Dr. Kamal Gulati
• The main components of ER models are
entities (things) and the relationships that can exist
among them.
• Entity–Relationship Modeling was developed
by Peter Chen and published in a 1976.

Dr. Kamal Gulati
The three schema approach to software
engineering uses three levels of ER models that
may be developed.
• Conceptual data model
• Logical data model
• Physical data model

Dr. Kamal Gulati
Conceptual data model
• A conceptual schema or conceptual data model is
a map of concepts and their relationships used
for databases.
• This describes the semantics of an organization
and represents a series of assertions about its
nature.
• Specifically, it describes the things of significance to
an organization (entity classes), about which it is
inclined to collect information, and characteristics
of (attributes) and associations between pairs of
those things of significance (relationships).

Dr. Kamal Gulati
CONCEPTUAL DATA MODEL
• This ER model establishes a broad view of what
should be included in the model set. Conceptual
data models:
• Include important entities and the relationship between
them.
• Do not specify attributes.
• Do not specify primary keys.
• Conceptual ERDs can be used as the foundation for
logical data models. They may also be used to form
commonality relationships between ER models as a
basis for data model integration.

Dr. Kamal Gulati
Logical data model
• Is a type of data model showing a detailed
representation of an organization's data,
independent of any particular technology, and
described in business language.
• A logical data model standardizes people, places,
things and the rules, relationships and the events
between them.

Dr. Kamal Gulati
LOGICAL DATA MODEL
• This model contains more detail than the conceptual ER
model, without regard to how information will be
physically implemented in the database. Logical data
models:
• Include all entities and relationships between them.
• Specify attributes for each entity.
• Specify primary key for each entity.
• Specify foreign keys, which identify the relationship between
different entities.
• Involve normalization, which is the process of removing
redundancy in a table so that the table is easier to modify.
Normalization typically occurs by dividing an entity table into
two or more tables and defining relationships between the
tables.

Dr. Kamal Gulati
Physical data model
• A physical data model (or database design) is a
representation of a data design which takes into
account the facilities and constraints of a
given database management system.
• In the lifecycle of a project it typically derives from
a logical data model, though it may be reverse-
engineered from a given database implementation.

Dr. Kamal Gulati
PHYSICAL DATA MODEL
• The physical data model represents the process of
adding information to the database. This model shows
all table structures, including column name, column
data type, column constraints, primary key, foreign key,
and relationships between tables. Physical data models:
• Specify all tables and columns.
• Include foreign keys to identify relationships between tables.
• May include denormalization, depending on user
requirements.
• May be significantly different from the logical data model.
• Will differ depending on which DBMS (database management
system) is used.

Dr. Kamal Gulati
Conceptual Data Model (CDM) Logical Data Model (LDM) Physical Data Model (PDM)
Includes high-level data constructs
Includes entities (tables), attributes
(columns/fields) and relationships (keys)
Includes tables, columns, keys, data types,
validation rules, database triggers, stored
procedures, domains, and access
constraints
Non-technical names, so that executives
and managers at all levels can understand
the data basis of Architectural Description
Uses business names for entities &
attributes
Uses more defined and less generic
specific names for tables and columns,
such as abbreviated column names,
limited by the database management
system (DBMS) and any company
defined standards
Uses general high-level data constructs
from which Architectural Descriptions are
created in non-technical terms
Is independent of technology (platform,
DBMS)
Includes primary keys, also all other keys
and indices for fast data access.
May not be normalized
Is normalized to fourth normal
form (4NF)
May be de-normalized to meet
performance requirements based on the
nature of the database. If the nature of the
database is Online Transaction
Processing (OLTP) or Operational Data
Store (ODS) it is usually not de-
normalized.
De-normalization is common in Data
warehouses.

Dr. Kamal Gulati
ERD (Entity Relationship Diagram)
• Logical representation of data in an organization.
• Views the entire system as a collection of entities
related to one another.

Dr. Kamal Gulati
Advantages of E-R Model

Dr. Kamal Gulati
Elements of E-R Diagram
• 1: Entity
• 2: Attributes
• 3: Relationships

Dr. Kamal Gulati
Entity
• An Entity is a Person, Place, Thing or Event for
which data is collected and maintained.
• Entities are represented in ER diagrams by a
rectangle and named using singular nouns.
Entity namesymbol

Dr. Kamal Gulati
Entity type/Entity class
• A set of entities with same attributes
• Example:
• Student entity class is a set of all students.
• Book entity type is for all Books etc.

Dr. Kamal Gulati
Entity instance / occurrence
• A member of an entity class is known as entity
instance .
• Also known as entity occurrence.

Dr. Kamal Gulati
Entity Class
Entity
instance

Dr. Kamal Gulati
Entity class
Entity instance

Dr. Kamal Gulati
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.

Dr. Kamal Gulati
• Example: Name, address, Class and Email of a
students are his attributes.
• Can you define for Employee?
Attribute name
Symbol

Dr. Kamal Gulati
Attribute Domain:
• A set of possible values for an attribute
• All attributes have domain
• Example :
• The domain for Grade point average
(GPA) can be from 0 to 4.
• Similarly, domain for Gender attribute can
be Either male or female.

Dr. Kamal Gulati
Types of Attributes
• 1: Simple
• 2: Composite
• 3: Single valued
• 4: Multi-valued
• 5: Derived

Dr. Kamal Gulati
• Cannot be subdivided into smaller
components.
PERSON
GENDER

Dr. Kamal Gulati
• Can be divided into smaller components.
EMPLOYEE
ADDRESS
street
city
country

Dr. Kamal Gulati
Single-valued Attributes:
Contain single valued value.
Employee
Gender
Multi-valued Attributes:
Contain two or more values.
person
name
city hobbies

Dr. Kamal Gulati
Multivalued Attribute
• If an attribute can have more than one value it is
called an multivalued attribute.
• It is important to note that this is different to an
attribute having its own attributes.
• For example a teacher entity can have multiple
subject values.

Dr. Kamal Gulati
Derived Attribute
• An attribute based on another attribute. This is
found rarely in ER diagrams.
• For example for a circle the area can be derived
from the radius.

Dr. Kamal Gulati
Relationship
• A relationship describes how entities interact. 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.

Dr. Kamal Gulati
The number of entities in a relationship
•Types:
1: Unary relationship
2: Binary relationship
3: Ternary relationship

Dr. Kamal Gulati
Unary Relationship
• It is also called as Recursive Relationship.
• If the same entity participates more than once in a
relationship it is known as a recursive relationship.
• For E.g: An employee can be a supervisor and be
supervised, so there is a recursive relationship.

Dr. Kamal Gulati
• Exist between the instances of two entity types.
• Types:
• 1: one-to-one
• 2:one-to-many
• 3:many –to-many

Dr. Kamal Gulati
• The maximum number of relationships.
*Circle means zero
*Line
means………..one
*Crow’s foot
symbol
means….many

Dr. Kamal Gulati
Relationship
• Cardinality and Ordinality are two other notations
used in ER diagrams to further define relationships.
• Cardinality specifies how many instances of an
entity relate to one instance of another entity.
Cardinality specifies the maximum number of
relationships and
• Ordinality specifies the absolute minimum number
of relationships.
• For example, a “student” is not to required to
“join” an “activity”. While an “activity” should be
participated by many “student”.

Dr. Kamal Gulati
Tips on How to Draw ER Diagrams
1. Identify all the relevant entities in a given system and
determine the relationships among these entities.
2. An entity should appear only once in a particular
diagram.
3. Provide a precise and appropriate name for each
entity, attribute, and relationship in the diagram.
4. Remove vague, redundant or unnecessary
relationships between entities.
5. Never connect a relationship to another relationship.
6. Make effective use of colors.

Dr. Kamal Gulati
Proprietary ER diagramming tools
• Avolution
• Creately
• ER/Studio
• ERwin
• DeZign for Databases
• LucidChart
• MagicDraw
• MEGA International
• ModelRight
• Navicat Data Modeler
• OmniGraffle
• Oracle Designer
• PowerDesigner
• Prosa Structured Analysis Tool
• Rational Rose
• Software Ideas Modeler
• Sparx Enterprise Architect
• SQLyog
• System Architect
• Toad Data Modeler
• Visual Paradigm
• yEd
• http://creately.com/ER-diagram-software

Dr. Kamal Gulati
Exam database ERD

Dr. Kamal Gulati
Car Rental System

Dr. Kamal Gulati
Hotel Reservation System

Dr. Kamal Gulati
Railway Reservation System

Dr. Kamal Gulati
Benefits of ER diagrams
• ER diagrams constitute a very useful framework for
creating and manipulating databases.
• First, ER diagrams are easy to understand and do not
require a person to undergo extensive training to be
able to work with it efficiently and accurately.
• Second, ER diagrams are readily translatable into
relational tables which can be used to quickly build
databases. In addition, ER diagrams can directly be
used by database developers as the blueprint for
implementing data in specific software applications.
• Lastly, ER diagrams may be applied in other contexts
such as describing the different relationships and
operations within an organization.

Dr. Kamal Gulati
employee
department
jobs
equipment
suppliers project

Dr. Kamal Gulati
name DOB
Phone no
Project
no
Project
name
Project
cost duration
name
Address
Date of last meeting
number

(Hope you are able to
understand the Fundamentals
of Data Modeling and Database
Design)
For More Questions /
Queries Feel Free to
Contact me.

Dr. Kamal Gulati
Associate Professor |
University Quality Support Head
Mentoring Programme Coordinator &
Exam Superintendent |
[Ph. D., M.Sc. (Computer Science), M.C.A., M.B.A]
Professional Certifications:
• Certified Microsoft Innovative Educator
• Data Science 101 Certification from Big Data University
• R Language 101 Certification from Big Data University
• SQL Certification from SOLOLEARN.com
• Certified IBM Big Data 101 from Big Data University
• R Program & Python Certified from DataCamp
• Wiley Certified Big Data Analyst [WCBDA]
• Certification on DBMS from IIT Mumbai
• Certified Cisco Certified Network Associate [CCNA]
• Certified Microsoft Certified Professional [MCP]
• Certified Brainbench in (MS Access, MS Project, MySQL 5.7 Administration, Computer
Fundamentals, Advanced Ms. Excel & Windows OS)
• Real-time Advertising Fundamentals Certified from RTA Academy

• Worked as Visiting Professor with Stratford University, USA for six months from Jan’2016 to
June’2016.
• Also worked at Bahrain University in Kingdom of Bahrain Sr. I.T. Faculty (Computer Science
Department) for Period of 2 Years.
• Have rich experience in the field of teaching and research in Computer Science and Information
Technology for almost 15+ years in Academia.
• Having experience of working with both private and public institutions and universities as the
lecturer and self-instruction material writer for Information Technology courses.
• Had number of research papers published in national and international journals and conference
proceedings in IEEE and Scopus Index.
• Also chaired various National and International Conferences of repute and associated with
various International Journals as Editorial Board Member for International and National,
Academic Adviser and Research Paper Reviewer.
• My current area of interest: Big Data Analytics, R Software, Internet & Web Technology, IT Project
Management, Decision Support System, Business Analytics, Management Information System,
Database Management System, Data Networking, R Software and Advanced Excel with Visual
Basic Macros.
• Country Visited: USA, Canada, UAE, Bahrain, Oman (Mostly for Teaching and Research Purpose)
Profile of Dr. Kamal Gulati

Profile Contd….
• Technical Program Committee for International Conference on Data, Engineering and Applications 2017
(IDEA-2k17) which would be on October 28-29, 2017 at Bhopal. http://www.ideaconference.in
• Advisory Board Committee Member for International Conference on Energy, Communication, Data
Analytics and Soft Computing (ICECDS) which would be on 1-2 August 2017 at SKR Engineering College,
Poonamallee, Tamil Nadu, India. http://ecds.org.in
• Advisory Committee Member for International Conference on Innovative Research in Engineering and
Science which would be on 16-17 June 2017 at Asian Institute of Technology Conference Center
Thailand. http://www.iresconf.org
• Advisory Committee Member for International Conference on Cloud Computing and Internet of
everything which held on 10-11 Feb’2016 at Delhi-NCR. http://www.ccioet.org
• Technical Committee member for InCITe-2016 (International Conference on Information Technology)
Theme - Internet of Things: Connect Your Worlds, IT Summit, Amity University 2016 which held on 06-07
Oct, 2016. http://www.amity.edu/incite2016
• Technical Speaker for Global perspective on IT business “The Changing Scenario” – Big Data on
International Students Conference New Delhi (ISCND) which held on 14-15 Oct, 2016 http://iscnd.com
• Advisory Committee Member for International Conference on Sustainable Computing Techniques in
Engineering, Science and Management which has held on 09-10 Sep’2016 at Delhi-NCR.
http://www.scesm.org
• Technical Program Committee Member for Program Committee Member for International Conference on
Recent Trends IN ICT, Jaipur, India, Aug 18-19, 2017 http://rtict.org
• Program Committee Member for International Conference on Recent Advancement in Computer and
Communication Bhopal, India, (IC-RAC-2017) May 26-27, 2017 http://www.icrac.co.in

Profile Contd….
• Editorial Board member for the following International Journals:
– International Journal of Computer Science and Innovation
http://www.infinitysciences.org
– International Journal of Latest Research in Engineering and Technology
http://www.ijlret.com
– International Journal of Latest Trends in Engineering and Technology
http://www.ijltet.org
– International Journal of Application or
Innovation in Engineering & Management
http://www.ijaiem.org
– International Journal for Management http://www.ijm-apm.com
– The International Journal of Emerging Engineering and Embedded Systems
http://www.ijeees.org
– Conference Info http://conferenceinfo.org/tpc.php
• Expert Speaker for Program “Insurance Beyond Doubt” Presented by Oriental
Insurance Co Ltd.
https://www.youtube.com/watch?v=GrvJkN_Zn3Q

BOOK, CHAPTER, and CASE STUDY Published
• Published Book on “A Study of Changing Trends in E-CRM of Indian
Insurance Industry” Published by LAP Lambert Academic Publishing, one
of the top researchers and renowned scientists of Germany with ISBN:
3330009543, 9783330009547. The Book available at Amazon.com.
• Published Real Case Study on “IoT Security Considerations for Higher
Education” published on Business Cases - RENVOI 2017 BOOK (The Case
Centre, UK) with ISBN: 978-1-4828-8840-9, Page 63-70. The Book available
at the various online website: Amazon, AbeBooks, Chegg, Barnes & Noble.
• Published Chapter on "Role of eWorld in Insurance Innovation" Published
by Insurance Institute of India (III), 60 Years Diamond Jubilee,
Compendium, Nov 2016 – (Magazine) – One of the premium Insurance
Institute of India.

Contact Details
• Email : drkamalgulati@gmail.com
• Website : http://mybigdataanalytics.com
• LinkedIn : https://in.linkedin.com/in/drkamalgulati
• Phone: +91-9718361928

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