1.
ELE275 (COMPUTER
APPLICATIONS I)
CONTENTS
 Identification, functions, applications, and use of PC parts and
peripheral devices.
 Safety Precautions and Preventive Maintenance of PC.
 Filling system: Word processing applications and use.
 Internet: available services, principle of operation, applications
and demonstrations.
 Spreadsheet: Applications, how to use. (Microsoft Excel)
 Database Management Package: Applications, demonstrations.
 Report presentation Software Packages:, applications,
demonstrations and use. (Microsoft PowerPoint)
 Mini-project to test proficiency in the use of the packages.
ELECTRICAL
AND
ELECTRONICS
ENGINEERING
DEPARTMENT,
UNIVERSITY
OF
ILORIN,
ILORIN

2.
LECTURE 02
Database Management Package: Applications, demonstrations.
OLAYANJU S. A.

3.
Introduction
 Today, more than at any previous time, the success of an
organization depends on:
• its ability to acquire accurate and timely data about its
operations,
• managing this data effectively,
• using it to analyze and guide its activities.
 Information processing is a rapidly growing multibillion
dollar industry.
 The amount of information available to us is literally
exploding.
 The value of data as an organizational asset is widely
recognized.
 Yet without the ability to manage this vast amount of data,
and to quickly find the information that is relevant to a
given question, as the amount of information increases, it
tends to become a distraction and a liability, rather than

4.
Introduction Contd.
 This paradox drives the need for increasingly
powerful and flexible data management systems.
 To get the most out of their large and complex
datasets, users must have tools that simplify the
tasks of managing the data and extracting useful
information in a timely fashion.
 Otherwise, data can become a liability, with the cost
of acquiring it and managing it far exceeding the
value that is derived from it.

5.
History of DBMS
 From the earliest days of computers, storing and
manipulating data have been a major application focus.
 The first general-purpose DBMS was designed by Charles
Bachman at General Electric in the early 1960s and was
called the Integrated Data Store.
 It formed the basis for the network data model, which was
standardized by the Conference on Data Systems
Languages (CODASYL) and strongly influenced database
systems through the 1960s.
 In the late 1960s, IBM developed the Information
Management System (IMS) DBMS, used even today in
many major installations.
 IMS formed the basis for an alternative data
representation framework called the hierarchical data
model.

6.
History Contd.
• In 1970, Edgar Codd, at IBM's San Jose Research
Laboratory, proposed a new data representation framework
called the relational data model. This proved to be a
watershed in the development of database systems: it
sparked rapid development of several
• Database systems matured as an academic discipline, and
the popularity of relational DBMSs changed the commercial
landscape.
• Their benefits were widely recognized, and the use of
DBMSs for managing corporate data became standard
practice.
• In the 1980s, the relational model consolidated its position as
the dominant DBMS paradigm, and database systems
continued to gain widespread use.
• The SQL query language for relational databases, developed
as part of IBM's System R project, is now the standard query
language.

7.
 DATA could mean:
• A fact or more specially a value of attribute of an entity.
• Raw material of Information in a form which can be
processed by a computer.
• A collection of facts and figures that can be processed to
produce information.
 An entity in general, may be a person, an object, idea,
event, condition or situation.
 An entity is represented by set of attributes. An attribute is
also referred to as data item, data element , data field
 An entity set is a set of entities of the same type that share
the same properties or attributes .
 A set of attributes describes an entity.
 For example : In a library environment,
Entity Set: Catalogue -
Entity: Books, Journals, Thesis, etc
Attributes: contains Author, Title, Imprint, ISBN, Publisher, etc

8.
 A database is an organized collection of related data stored with
minimum redundancy, in a manner that makes them accessible for
multiple application
 A database management system (DBMS) is a software system
that allows access to data contained in a database.
 The objective of the DBMS is to provide a convenient and effective
method of defining, storing and retrieving the information
contained in the database.
 The DBMS interfaces with the application programs, so that the
data contained in the database can be used by multiple
applications and users.
 In addition, the DBMS exerts centralized control of the database,
prevents fraudulent or unauthorized users from accessing the
data, and ensures the privacy of the data
 Characteristics of DBMS
• Real-world entity: A modern DBMS is more realistic and uses
real-world entities to design its architecture. For example, a
school database may use students as an entity and their
age as an attribute.

9.
• Relation-based tables: DBMS allows entities and relations
among them to form tables.
• Isolation of data and application: A database system is
entirely different than its data. A database is an active entity,
whereas data is said to be passive, on which the database
works and organizes.
• Less redundancy: DBMS follows the rules of
normalization, which splits a relation when any of its
attributes is having redundancy in values. Normalization is
a mathematically rich and scientific process that reduces
data redundancy.
• Consistency: a state where every relation in a database
remains consistent. There exist methods and techniques,
which can detect attempt of leaving database in
inconsistent state.
• Query Language: DBMS is equipped with query language,
which makes it more efficient to retrieve and manipulate
data. A user can apply as many and as different

10.
• Multiuser and Concurrent Access: DBMS supports
multi-user environment and allows them to access and
manipulate data in parallel.
• Multiple views: DBMS offers multiple views for
different users. A user who is in the Sales department will
have a different view of database than a person working in
the Production department. This feature enables the
users to have a concentrate view of the database according
to their requirements.
• Security: Features like multiple views offer security to
some extent where users are unable to access data of
other users and departments. DBMS offers methods to
impose constraints while entering data into the database
and retrieving the same at a later stage.

11.
DBMS USERS
Administrators:
• Maintain the DBMS and are responsible for administrating the
database.
• Are responsible to look after its usage and by whom it should
be used.
• Create access profiles for users and apply limitations to
maintain isolation and force security.
• Also look after DBMS resources like system license, required
tools, and other software and hardware related maintenance.
Designers:
• People who actually work on the designing part of the
database.
• They keep a close watch on what data should be kept and in
what format.
• They identify and design the whole set of entities, relations,
constraints, and views.
End Users:

12.
ARCHITECTURE
 The design of a DBMS depends on its architecture.
 It can be centralized, decentralized or hierarchical.
 The architecture of a DBMS can be seen as either single tier or
multi-tier.
 An n-tier architecture divides the whole system into related
but independent n modules, which can be independently
modified, altered, changed, or replaced.
 In1-tier architecture, the DBMS is the only entity where the
user directly sits on the DBMS and uses it.
• Any changes done here will directly be done on the DBMS
itself.
 If the architecture of DBMS is 2-tier, then it must have an
application through which the DBMS can be accessed.
• Programmers use 2-tier architecture where they access the
DBMS by means of an application.
• Here the application tier is entirely independent of the
database in terms of operation, design, and programming.

13.
3 - tier Architecture
A 3-tier architecture separates its tiers from each other based on
the complexity of the users and how they use the data present in
the database.
Database (Data) Tier:
• At this tier, the database resides along with its query
processing languages.
• We also have the relations that define the data and their
constraints at this level.
Application (Middle) Tier:
• At this tier reside the application server and the programs that
access the database.
• The application layer sits in the middle and acts as a mediator
between the end-user and the database.
User (Presentation) Tier:
• End-users operate on this tier At this layer, multiple views of the
database can be provided by the application.
• All views are generated by applications that reside in the
application tier.

14.
DATA MODELS
 Data models define how:
• the logical structure of a database is modeled.
• data is connected to each other
• they are processed and stored inside the system.
 Data Models are fundamental entities to introduce abstraction
in a DBMS.
Types
A. Entity-Relationship Model
Entity-Relationship (ER) Model is based on the notion of real-
world entities and relationships among them. While formulating
real-world scenario into the database model, the ER Model
creates entity set, relationship set, general attributes, and
constraints.
ER Model is best used for the conceptual design of a database.
ER Model is based on:
Entities and their attributes.
Relationships among entities.

15.
ER Model

16.
 Entity: An entity in an ER Model is a real-world entity having
properties called attributes. Every attribute is defined by its set
of values called domain.
For example, in a school database, a student is considered as an
entity.
Student has various attributes like name, age, class, etc.
Relationship: The logical association among entities is called
relationship. Relationships are mapped with entities in various
ways.
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

17.
Derived attribute: The attributes that do not exist in the physical
database, but their values are derived from other attributes
present in the database. For example, age can be derived from
date of birth.
Single-value attribute: Contain single value. For example:
account number.
Multi-value attribute: May contain more than one values. For
example, a person can have more than one phone number, Email
address, etc.
Entity-Set and Keys
Key is an attribute or collection of attributes that uniquely identifies
an entity. (E.g. a student’s matric number.) among entity set.
• 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

18.
ER DIAGRAM REPRESENTATION
Entities are represented by means of rectangles. Rectangles are
named with the entity set they represent.
Entities in a school database
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.
Simple attributes of an entity.
STUDENTS TEACHERS PROJECTS
STUDENTS
MATRIC. N0.
NAME
LEVEL

19.
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.
Composite attributes of an entity.
STUDENTS
MATRIC. N0.
NAME
LEVEL
FIRST NAME
LAST NAME

20.
Multivalued attributes are depicted by double ellipse.
STUDENTS
MATRIC. N0.
NAME
LEVEL
FIRST NAME
LAST NAME
PHONE N0.

21.
Derived attributes are depicted by dashed ellipse.
STUDENTS
MATRIC. N0.
NAME
LEVEL
FIRST NAME
LAST NAME
PHONE N0.
AGE

22.
Relationship
Relationships are represented by diamond-shaped box. Name of
the relationship is written inside the diamond-box. All the entities
(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.
• 1 1
Entity
Relationshi
p
Entity

23.
One-to-many: When more than one instance of an entity is
associated
with a relationship, it is marked as '1:N'.
1 N
Many-to-one: When more than one instance of entity is
associated with the relationship, it is marked as 'N:1'.
N 1
Many-to-Many: 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.
Entity
Relationshi
p
Entity
Entity
Relationshi
p
Entity
Entity
Relationshi
p
Entity

24.
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
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.
Entity
Relationshi
p
Entity
Total Participation Partial Participation

25.
Specialization
The opposite of generalization. In specialization, a group of
entities is divided into sub-groups based on their characteristics.
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.

26.
B. Relational Model: A very simple and elegant model; here, a
database is a collection of one or more relations, where each
relation is a table with rows and columns.
 This simple tabular representation enables even novice users
to understand the contents of a database.
 It permits the use of simple, high-level languages to query the
data.
 The major advantages of the relational model over the older
data models are:
• its simple data representation
• the ease with which even complex queries can be
expressed.
Concepts
Tables: In relational data model, relations are saved in the format
of Tables. This format stores the relation among entities. A table
has rows and columns, where rows represent records and
columns represent the attributes.
Tuple: A single row of a table, which contains a single record for

27.
Relational Model
MATRIC. NO. NAME AGE LEVEL DEPARTMENT PHONE N0.
13/30GC297 Trump 29 500 ELECTRICAL 0801234567
8
14/30GD876 Macron 26 400 MECHANICAL 0901234567
8
15/30GP765 Markel 24 300 BIOMEDICAL 0701234567
8
16/30GQ612 Buhari 22 200 WATER 0811234567
8
17/30GM531 Atiku 20 100 CHEMICAL 0911234567
8
Attributes
Column
Tuple

28.
Relation instance: A finite set of tuples in the relational database
system represents relation instance. Relation instances do not
have duplicate tuples.
Relation schema: A relation schema describes the relation name
(table name), attributes, and their names.
Relation key: Each row has one or more attributes, known as
relation key, which can identify the row in the relation (table)
uniquely.
Attribute domain: Every attribute has some predefined value
scope, known as attribute domain.
Constraints
Every relation has some conditions that must hold for it to be a
valid relation. These conditions are called Relational Integrity
Constraints. There are three main integrity constraints:
Key constraints
Domain constraints
Referential integrity constraints

29.
Key Constraint: There must be at least one minimal subset of
attributes in the relation, which can identify a tuple uniquely.
• In a relation with a key attribute, no two tuples can have
identical values for key attributes.
• a key attribute cannot have NULL values.
Key constraints are also referred to as Entity Constraints.
Domain Constraints
Attributes have specific values in real-world scenario. For
example, age can only be a positive integer. For example, age
cannot be less than zero and telephone numbers cannot contain a
digit outside 0-9.
Referential Integrity Constraints
Referential integrity constraints work on the concept of Foreign
Keys. A foreign key is a key attribute of a relation that can be
referred in other relation. Referential integrity constraint states that
if a relation refers to a key attribute of a different or same relation,
then that key element must exist.

30.
The main highlights of this model are:
• Data is stored in tables called relations.
• Relations can be normalized.
• In normalized relations, values saved are atomic values.
• Each row in a relation contains a unique value.
• Each column in a relation contains values from a same domain.

31.
RELATIONAL ALGEBRA
A procedural query language, which takes instances of relations
as input and yields instances of relations as output. It uses
operators to perform queries. The fundamental operations of
relational algebra are as follows:
Select
Project
Union
Set different
Cartesian product
Rename
Select Operation (σ)
It selects tuples that satisfy the given predicate from a relation.
Notation: σp(r)
Where σ stands for selection predicate and r stands for relation. p
is
prepositional logic formula which may use connectors like and, or,
and not. These terms may use relational operators like: =, ≠, ≥, <,

32.
example:
σsubject="database"(Books)
Output: Selects tuples from books where subject is 'database'.
σsubject="database" and price="450"(Books)
Output: Selects tuples from books where subject is 'database'
and 'price' is 450.
σsubject="database" and price < "450" or year > "2010"(Books)
Output: Selects tuples from books where subject is 'database'
and 'price' is 450 or those books published after 2010.
Project Operation (Π): It projects column(s) that satisfy a given
predicate.
Notation: ΠA1, A2, An (r)
Where A1, A2, An are attribute names of relation r. Duplicate rows
are automatically eliminated, as relation is a set. Example
Πsubject, author (Books)
Selects and projects columns named as subject and author from
the relation Books.

33.
Selects and projects columns named as subject and author from
the relation Books.
Notion: r U s
Where r and s are either database relations or relation result set
(temporary
relation).
For a union operation to be valid, the following conditions must
hold:
r and s must have the same number of attributes.
Attribute domains must be compatible.
Duplicate tuples are automatically eliminated.
Example
Π author (Books) ∪ Π author (Articles)
Output: Projects the names of the authors who have either written
a book or an article or both.
Set Difference (−)
The result of set difference operation is tuples, which are present
in one relation but are not in the second relation.

34.
Πauthor(Books) − Πauthor(Articles)
Output: Provides the name of authors who have written books but
not articles.
Cartesian Product (Χ)
Combines information of two different relations into one.
Notation: r Χ s
Where r and s are relations and their output will be defined as:
r Χ s = { q t | q ∈ r and t ∈ s}
Examlle
Πauthor = 'tutorialspoint'(Books Χ Articles)
Output: Yields a relation, which shows all the books and articles
written by tutorialspoint.
Rename Operation (ρ)
The results of relational algebra are also relations but without any
name. The rename operation allows us to rename the output
relation. ‘rename’ operation is denoted with small Greek letter rho
ρ.
Notation: ρ x (E)

35.
S/
N
SUBJECT PRICE YEAR OF
PUBLICATION
AUTHOR
1 Physics 150 2005 Kim James
2 Database 450 2007 Putin Clarke
3 Database 450 2010 Trump Granny
4 Database 1250 2012 Macron Bill
1. Using the table given above, what will be the serial number of
tuples selected as the output of operation: σsubject ‘database and
price’ = ‘450’ (Books)[ A. 1 only B. 2 &3 only C. 2, 3 &4 D. None
of the above]
2. The output of operation: σsubject = “database” and price < “450” or year>
“2010” (B00ks) is [A. 3 only B. 2 &3 only C. 2, 3 &4 D. None of
the above]

36.
References:
1. DBMS @ www.tutorialspoint.com
2. Raghu Ramakrishman and Johannes Gehrke, Database Management System
second edition available online @ http://www.cs.wisc.edu/~dbbook
3. Database Fundamentals: Johns Hopkins University rrobbins@gdb.org
4. Database Systems: Concept and design by Bhojaraju G. and M.M.Koganurmath
Mumbai India.