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BY ADIL ASLAM

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 Database
• An organized collection of logically related data.
 Data
• A stored representation of objects and events that
have meaning
 Meaningful facts
 Data no context
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 Types of data :
Data
Structured Unstructured
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 Structured Data
• Structured data are facts concerning
objects and events.
• The most important structured data are
numeric, text , character, and dates.
Structured data are stored in tabular form.
• Examples
 Number
 Dates
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 Unstructured Data
• Unstructured data are multimedia data such as
documents, photographs, maps, images,
sound, and video clips.
• Unstructured data are most commonly found on
Web servers and Web-enabled databases.
• Examples
 images
 video
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 Information :
• Data processed to increase knowledge in the
person using the data.
• Data that has been processed to make it
useful.
• The foundation of correct decisions.
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Data
 Raw facts
 No context
 Just numbers and
text
Information
 Data with context
 Processed data
 Value-added to data
 Summarized
 Organized
 Analyzed
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 Difference between data and information
with example
 5/10/07
 1$
 5/10/07 date of your final exam
 1$ Price of sugar of one kg
Example of
data
Example of
Information
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Data Information
 6.34
 6.45
 6.39
 6.62
 6.57
 6.64
 6.71
 6.82
 7.12
 7.06
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 Metadata:
• Data that describe the properties and context
of user data.
• “Data about data”
• Metadata is a piece of information describing
a resource.
• Examples of resources are books, web sites,
and videos.
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 Examples of Metadata
Example of metadata for class Roster
Descriptions of the properties or characteristics of the data,
including data types, field sizes, allowable values, and data
context
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 Database
 Database is a centralized, and organized
collection of some logically related
organizational data.
 In database, data is organized using some
Data Model
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 Data Model
 Data Model is collection of concepts and
theories used to organize data
 Common data models are
▪ Network,
▪ Relational,
▪ Object Oriented ,
▪ Object Relational etc.
 In short, we use some data model to
organize data or build database
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 File-based System
• File-based systems were an early attempt to
computerize the manual filing system. File-
based system is a collection of application
programs that perform services for the end-
users. Each program defines and manages its
data.
• However, five types of problem are occurred in
using the file-based approach:
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 Example of FBS
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 Example of FBS
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Student Applied
Course Data
Faculty Payroll
data
Dean Faculty
Data
Merit calculation
Program
Student Scheduling
Faculty Scheduling
Payroll
Merit List
Class List
Final Faculty
Schedule
Pay Checks
Files
Programs
University Environment
Output
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 Disadvantages of File Processing
 Program-Data Dependence
 All programs maintain metadata for each file they use
 Duplication of Data
 Different systems/programs have separate copies of the same data
 Limited Data Sharing
 No centralized control of data
 Lengthy Development Times
 Programmers must design their own file formats
 Excessive Program Maintenance
 80% of information systems budget
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 Problems with Data Dependency
• Each application programmer must maintain
his/her own data.
• Each application program needs to include
code for the metadata of each file.
• Each application program must have its own
processing routines for reading, inserting,
updating, and deleting data
• Lack of coordination and central control
• Non-standard file formats
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 SOLUTION: The DATABASE Approach
 The DATABASE Approach
 Database approach is a computer based
storage technology in which related data is
shared by various application programs
 Central repository of shared data
 Data is managed by a controlling agent
 Requires a Database Management System
(DBMS)
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 Database Management System
• A database management system (DBMS) is a
software package designed to define,
manipulate, retrieve and manage data in a
database.
 Basic functions:
• Multiple user interfaces
• Controlled redundancy
• Common RDBMS are Oracle, SQL Server, MySql,
Access, Sybase etc.
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 Database Management System
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Student Applied
Course Data
Dean Faculty
Data
Dean Faculty
Data
Faculty Payroll
data
Merit calculation
Program
Student Scheduling
Faculty Scheduling
Payroll
Merit List
Class List
Final Faculty
Schedule
Pay Checks
DBMS
University Environment
Database Programs Output
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 Advantages of the Database Approach
• Program-Data Independence
• Minimal data redundancy
• Improved data sharing
• Improved data quality
• Improved data accessibility or Better Data Accessibility
• Reduced program maintenance
• Improved data consistency
• Reduced duplication of data
• Increased productivity of application development
• Providing backup and recovery services
• Improved decision support
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 Disadvantages
 Complexity
 Database management system is an extremely complex
piece of software. All parties must be familiar with its
functionality and take full advantage of it. Therefore,
training for the administrators, designers and users is
required.
 Size
 The database management system consumes a
substantial amount of main memory as well as a large
number amount of disk space in order to make it run
efficiently.
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 Cost of DBMS
 A multi-user database management system may be
very expensive. Even after the installation, there is a
high recurrent annual maintenance cost on the
software.
 Cost of conversion
 When moving from a file-base system to a
database system, the company is required to have
additional expenses on hardware acquisition and
training cost.
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 Elements of the Database Approach
 Data models
▪ Graphical system capturing nature and relationship of
data
• Enterprise Data Mode
▪ High-level entities and relationships for the
organization
▪ Project Data Model
▪ More detailed view, matching data structure in
database
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 Entities
▪ Noun of describing of a person , place ,object , or
event
 Composed attributes
 Relationship
▪ Between entities
▪ Usually one to many (1:M) or many to many (M:M)
• Relational Databases
 Database technology involving tables
 Representing entities
 Representing relationships
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 Comparison of enterprise and project level data
model
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 Components of the Database Environment
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 Components of the Database Environment
• A database management system (DBMS) consists of
several components. Each component plays very
important role in the database management system
environment. The major components of database
management system are:
 1:Computer-aided software engineering (CASE) tools
• CASE tools are automated tools used to design databases
and application programs.
• These tools help with creation of data models.
 2:Repository
 Centralized storehouse of metadata
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 3:Database Management System (DBMS)
 Software for managing the database
 4:Database
 Storehouse of the data
 It is important to distinguish between the database and
the repository.
 The repository contains definitions of data, whereas
the database contains occurrences of data
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 5:Application programs
 Computer-based application programs are used to
create and maintain the database and provide
information to users.
 6:User interface
 Text and graphical displays to users
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 7:Data/Database Administrators
 A person who is responsible for managing the
overall database management system is called
database administrator or simply DBA.
 8:System Developers
 Personnel responsible for designing databases and
software
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 9:End users
 The end-users are the peoples who interact with
database management system to perform different
operations on database such as retrieving, updating,
inserting, deleting data etc.
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 The Range of Database Applications
 Personal databases
 Workgroup databases
 Departmental/divisional databases
 Enterprise database
 Enterprise resource planning (ERP) systems
 Data warehousing implementations
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 The Range of Database Applications
 Personal Database – standalone desktop
database
 Workgroup Database – local area network
(<25 users)
 Department Database – local area network
(25-100 users)
 Enterprise Database – wide-area network
(hundreds or thousands of users)
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 PC databases:
 Personal database approach is designed to support to
store and to maintain the personal information. It can
access by one user only. In general we can store
personal database in personal computers like laptops,
cellular phones etc. We have major problem with
personal database approach that is it does not allow
sharing of the data i.e. the personal database
is working based on the stand-alone mode.
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Typical data from
a personal database
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 Work Group databases:
 In work group database approach , consists 20-25
members those team of people will develop a database of an
organization . The work group database is designed to
support to maintain database by a group of people.
 Work group database provides data sharing . In general
work group database in LAN group network where
database is available in one system this system is known
as database Server .Database server is connected with 10
or more than 10 users .This type of architecture is known as
one type of client/server architecture
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 Departmental databases:
 Departmental database approach is designed to
support to maintain departmental wise activities in an
organization. It consist department information ,
procedures and functions.
 In departmental database consist 50-100 persons to
perform a task. In an organization contain its
department database server in an organization . The
department database are connected to maintain from
the main server to connect the database departmental
database server , distributed the information to
department and users . This technology is called as two
tier database architecture.
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 Example
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 Enterprises databases:
 Enterprise database approach is designed to support to maintain
organization database . It not only control the organizational
database but also making decisions to support the database . It
perform all the activities of an organization. The education of
enterprise database approach two major departments these are
 Enterprise Resource Planning System (ERPS)
 Data warehousing .
 ERPS is developed from MRP(Material Requirement Planning )
system .These system contains some functions such as how to
distribute the data to entire organization and how to control the flow
of data in an enterprise / organization .In an enterprise database
we have entire organization database or information and historical
information about the organization and collaboration organization
information such enterprise database organization is known as data
ware housing.
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1960s
Files processing
system remain
dominant in this
decade
First database
system developed
during this
1970s
Hierarchical and
Network
Commercial use of
DBMS
Relational Model was
first defined by E.F
Codd
1980s
Relational model was
famous and widely in
use(2nd generation of
DBMS)
Beginning of
SQL(Structure Query
Language)
1990
Common use of
different types of
data like graphics,
sound, images, and
video
Relational and
object-oriented
databases are of
great importance
today
Some vendors are
developing combined
databases(object-
relational)
2000 and
Beyond
Data-mining and
Distributed DBMS
Data Warehousing
and Mining
Big Data & Big Data
Analytics
Evolution Of Databases
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 Evolution of DB Systems
 Flat files - 1960s - 1980s
 Hierarchical – 1970s - 1990s
 Network – 1970s - 1990s
 Relational – 1980s - present
 Object-oriented – 1990s - present
 Object-relational – 1990s - present
 Data warehousing – 1980s - present
 Web-enabled – 1990s - present
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 Evolution Of Databases
 Greater independence between programs and
data
 Manage increasingly complex data types and
structures
 The desire to provide easier and faster access
to data for users
 The need to provide ever more powerful
platforms for decision support applications
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 Evolution Of Databases
 1960s
 Files processing system remain dominant in this
decade
 First database system developed during this
 1970s
 Hierarchical and Network
 Commercial use of DBMS
 Relational Model was first defined by E.F Codd
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 Evolution Of Databases
 1980s
 Relational model was famous and widely in use(2nd
generation of DBMS)
 Beginning of SQL(Structure Query Language)
 1990s
 Common use of different types of data like graphics,
sound, images, and video
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 Evolution Of Databases
 Relational and object-oriented databases are
of great importance today
 Some vendors are developing combined
databases(object-relational)
 2000 and Beyond
 Data-mining and Distributed DBMS
 Data Warehousing and Mining
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 Enterprise Data Model
 First step in database development
 Specifies scope and general content
 Overall picture of organizational data at high
level of abstraction
 Entity-relationship diagram
 Descriptions of entity types
 Relationships between entities
 Business rules
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Segment from enterprise data model
Enterprise data model
describes the high-
level entities in an
organization and the
relationship between
these entities
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 Information Systems Architecture (ISA)
 Conceptual blueprint for organization’s desired
information systems structure
 Consists of:
 Data (e.g. Enterprise Data Model – simplified ER Diagram)
 Processes – data flow diagrams, process decomposition, etc.
 Data Network – topology diagram (like fig 1.9)
 People – people management using project management tools
(Gantt charts, etc.)
 Events and points in time (when processes are performed)
 Reasons for events and rules (e.g. decision tables)
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 Two Approaches to Database and IS
Development
 SDLC
 System Development Life Cycle
 Detailed, well-planned development process
 Time-consuming, but comprehensive
 Long development cycle
 Prototyping
 Rapid application development (RAD)
 Cursory attempt at conceptual data modeling
 Define database during development of initial prototype
 Repeat implementation and maintenance activities with
new prototype versions
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 SDLC(Systems Development Life Cycle )
 The Systems Development Life Cycle (SDLC) is a
process used in the development, creation, and
maintenance of an information system.This
process is often used in the creation or updating
of a database system.
 The SDLC has five phases:The Planning phase,
the Analysis phase, the Design phase, the
Implementation phase, and the Maintenance.
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
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Planning:
 Identify and select the system for development
 Assess project feasibility
 Develop the project plan
Analysis:
 Gather business requirements
 Create process diagrams
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 Design:
 Determine technical systems configuration
 Determine data structure
 Design system models
 Set systems conversion plan
 Development:
 Develop the IT infrastructure
 Develop the database and programs
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 Testing:
 Write the test conditions
 Perform the system testing
 Implementation:
 Determine implementation method
 Provide training for the system users
 Write detailed user documentation
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
Planning Purpose–preliminary understanding
Deliverable–request for study
Database activity–
enterprise modeling and
early conceptual data
modeling
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
Analysis
Purpose–thorough requirements analysis and
structuring
Deliverable–functional system specifications
Database activity–thorough
and integrated conceptual
data modeling
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical DesignLogical Design
Purpose–information requirements elicitation
and structure
Deliverable–detailed design specifications
Database activity–
logical database design
(transactions, forms,
displays, views, data
integrity and security)
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
Physical Design
Purpose–develop technology and
organizational specifications
Deliverable–program/data
structures, technology purchases,
organization redesigns
Database activity–
physical database design (define
database to DBMS, physical
data organization, database
processing programs)
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
Implementation
Purpose–programming, testing, training,
installation, documenting
Deliverable–operational programs,
documentation, training materials
Database activity–
database implementation,
including coded programs,
documentation,
installation and conversion
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
Maintenance
Purpose–monitor, repair, enhance
Deliverable–periodic audits
Database activity–
database maintenance,
performance analysis
and tuning, error
corrections
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Identify Project
Initiate and Plan
Analyze
Logical Design
Physical Design
Implementation
Maintenance
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Database Development
Activities
SDLC
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 Design methodology which speeds systems
delivery through a combination of speedy
design iterations, data modeling, user/developer
teamwork, and automated development tools.
 Encompasses a set of techniques that can be
used to build complex, strategic, and mission-
critical applications in months rather than years
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