The document discusses the history and evolution of database management systems from the 1960s to present. It covers early stages like organizational databases in the 1960s, the introduction of the relational model in the 1970s, object-oriented databases in the 1980s, client-server applications in the 1990s, and internet-based databases in the 2000s. It also describes some common database components, models, and relationships.

1. MODULE 1
DATABASE MANAGEMENT SYSTEMS

2. HISTORY OF DATABASE
PROCESSING

3. STAGES
• Organizational Context (1960)
• Relational Model (1970)
• Object Oriented DBMS (1980)
• Client Server Database Application (1990)
• Database using internet Technology (200)

4. Organizational Context (1960)
Used to solve file processing
Difficulty in managing data
Difficulty in developing new systems
Limitations in Integration of data
Started
Organization Companies started developing large
wide database
Database Started centralizing operational data
Application

5. Limitations
• Limited Technology
• New Technology
• Slow Applications
• Unreliable Applications
• Difficulty in Handling large Volume of Data
• Slow Transactions
• Unreliability of Database

6. What made the situation to improve ?
• More Education on Hardware and Software
• More experts evolved
• New methods of: controlling data
: protecting data
: backing of database

7. Evolutions
Navigational
Parent
DBMS
Root
Integrated Data
Store
(Charles Bachman)
IMS
By: IBM

8. Relational Model (1970)
• Used application of mathematics: Relational
Algebra
• Used to reduce the problem of storing large
amount of data
• Developed by E.F.Codd

10. Benefits
• Minimizes duplication
• Eliminates processing & storing Errors
• Data stored as tables: rows & columns
• Concept of normalization used
• Columns of 1 row relates the entities

11. Order Customer Customer Item
Number First Name Last Name
A1010 John Markose Chair
A1011 Martin Baby Tables
A1012 Thomas Stephen Cupboard
A1013 Peter Edwin Computer

12. Resistance to Relational Model
• Requires more computer resources
• Makes the system slow
• Impractical with less speed processing capacity
• Examples: INGRES,
PRTV,
Business System 12
Alphora Dataphor,
Rel

13. Object oriented DBMS
An object-oriented database management
system (OODBMS), sometimes shortened to
ODBMS for object database management
system), is a database management system
(DBMS) that supports the modelling and
creation of data as objects.

14. What is an object ?
• objects are key to understanding object-
oriented technology
• Examples:
• dogs have
• state (name, color, breed, hungry)
and
• dogs have behavior (barking, fetching, and
slobbering )

15. Examples:
• Bicycles have
• state (current gear, current pedal cadence,
two wheels, number of gears)
and
• behavior (braking, accelerating, slowing down,
changing gears).

16. Object
• Definition: An object is a software bundle of
variables and related methods.

17. Drawbacks
• Difficult to use
• Very expensive to develop
• Already data in relational model needs
conversion
• More suitable for engineering application

18. Client Server Database Application
(1990)
• A client/server application is a piece of
software that runs on a client computer and
makes requests to a remote server.
• “Client/server systems operate in a networked
environment, splitting the processing of an
application between a front-end client and a
back-end processor.”

19. Basic Elements
• A CSDB system consists of three primary
software components:
• the client application (also called the front
end),
• the data access layer (also called middleware),
and
• the database server (also called a database
engine, DBMS, data source, or back end).

21. Client Application
• The client application is responsible
for accepting input from the user,
submitting a query to the database
server based on that input, receiving
results from the server, formatting
them, and presenting them to the
user.

22. Data Access Layer
The data access layer is relatively
transparent to the user, but may be
very apparent to the developer of
the client app. It provides for the
application and API used to submit
queries to a data source .

23. Database Server
The database server accepts queries
from clients, processes them
concurrently, and returns results.
There are a number of different
query languages around, by far the
most prevalent of which is SQL

24. Problems
Technical Support
Security
Connectivity

25. Database Models
• Hierarchical DBMS Model
• Network DBMS Model
• Relational DBMS Model
• Object Oriented DBMS Model
• Multi dimensional DBMS Model

26. • The hierarchical data model organizes data in a
tree structure.
• There is a hierarchy of parent and child data
segments.
• This structure implies that a record can have
repeating information, generally in the child data
segments.
• Data in a series of records, which have a set of
field values attached to it.
• It collects all the instances of a specific record
together as a record type.
• These record types are the equivalent of tables in
the relational model, and with the individual
records being the equivalent of rows.

28. A hierarchical database consists of the following:
• It contains nodes connected by branches.
• The top node is called the root.
• If multiple nodes appear at the top level, the
nodes are called root segments.
• The parent of node is a node directly above a
node
• Each node (with the exception of the root) has
exactly one parent.
• The child of node is the node directly below the
node and connected by a branch.
• One parent may have many children.

29. Network Model
• The network database organizes data in a
network structure.
• Any column in the network structure can be
linked to any other like a tree structure.
• A network structure can be described in
terms of parents and children.
• This model allows having more than one
parent.

31. Network Model
• Network DBMS have found not much more
acceptance than the hierarchical DBMS.
• They have the same flexibility limitations as
hierarchical database:
• the more powerful structure for representing
data relationships allows a more realistic
modeling of geographic phenomena.
• However network database tend to become
overlay complex too easily.

32. Relational Model
• The relational database organizes data in
tables.
• Each table is identified by a unique table
name, and is organized by rows and columns.
• Each column within a table also has a unique
name. Columns store the values for a specific
attribute
• Rows represent one record in the table.

34. Properties of Relational Tables:
• Values Are Atomic
• Each Row is Unique
• Column Values Are of the Same Kind
• The Sequence of Columns is Insignificant
• The Sequence of Rows is Insignificant
• Each Column Has a Unique Name

35. One-to-one Relationship-
• One-to-one Relationship-
Here one and only one record in the
destination table is related to one and only
one record in the source table.

36. One to one relationship

37. One-to-Many Relationship-
• This means that one record in the destination
table may be related to more than one record
in the source

38. One-to-Many Relationship-

39. Many-to-One Relationship
• This type of relationship is just opposite to the
One-to-Many Relationship. Here two or more
records in the destination table may be
related to one record in the source table.

40. Many-to-One Relationship

41. Object Oriented Model
• The object oriented data model manages data
through object.
• An object is a collection of data elements and
operations that together are considered as
single entity.

42. Multi Dimensional Database Model
• A multidimensional database (MDB) is a type
of database that is optimized for data
warehouse and online analytical processing
(OLAP) applications.
• Multidimensional databases are frequently
created using input from existing relational
databases. Whereas a relational database is
typically accessed using a Structured Query
Language (SQL)

44. DATABSE COMPONENTS
• Data Repository • System Software
• DBMS • Network Application
• Hardware • Front Tools
• Procedure Interface • Users
• Application Software
• Practitioners
• Data Dictionary

45. APPLICATION INTERFACE
USERS
PRACTIONERS
PROCEDURE INTERFACE
QUERY
APPLICATION REPORTING
SOFTWARE FRONT END
TOOLS
DATABASE
DATA DATA
COMPON- REPOS DBMS DICTIO
NARY
ENTS ITORY
HARDWARE

46. Data Repository
• Data Repository is a logical (and sometimes
physical) partitioning of data where multiple
databases which apply to specific applications
or sets of applications reside.

47. Procedure interface
• The characteristics of a procedure that is
executed on the database
• Example
SQL:>/ CREATE TABLE <Table name>

48. Data Dictionary
• A data dictionary is a collection of descriptions
of the data objects or items in a data model
for the benefit of programmers and others
who need to refer to them.

49. Data dictionary : sample

50. Database Development Process

51. Enterprise data modelling
• Is the first step in database development, in
which the scope and general contents of
organisational databases are specified
• Graphical representation of data used by an
enterprise or company
• Gives a helicopter view of the data and data
transactions of the organisation
•

52. Enterprise data modelling
• Data model encompass both current and historical data of
the organisation
• The model should reflect both the data and the processes
of the organisation, plus the views of these components
required by the various sections of the organisation.
• Example:
• sales data (invoices etc.) will be viewed from a monetary
aspect by the accountant, from a quantitative aspect by the
store staff and from both these aspects by the marketing
people

53. Information System Architecture (ISA)
6 Key Components:
1. Data
2. Process
3. Network
4. People
5. Events and points in Time
6. Reason

54. 1. Data
The processed information
The information that need to be exchanged,
recorded, processed and verified, and
classified and stored.

55. 2. Process
• The event that manipulates the data
Example:
Pos (Point of Sales): Billing of items
Bank : withdrawal or deposit of money by a
customer

56. 3. Network
• Network transports the data around
the organization and between the
organizations and the key business
partners.

57. 4. People
• The entities who perform the process
• They are the source of information and
receiver of information
Example:
Pos: Sender of information: Billing clerk
Receiver of Information: Store manager

58. 5. Events and points in time

59. 6. Reasons
• Reasons for events
• Rules that govern the process
• Example: Customer cash withdrawal at ATM

60. ATM transaction
Sl. No Event Process Action
1 Enter Pin Verify Pin Authorize
2 Enter Choose Authenticate
Transaction Transaction
Type
3 Enter Verify Allow
Amount balance Withdrawal

61. enterprise data model (Pine Valley Furniture Company)

62. Information Engineering
• “A data-oriented methodology to create and maintain
information systems.”
• Top-down planning approach.
• Four steps:
– Planning (Results in an Information Systems Architecture)
– Analysis – meet the various members of the organisation
(from top to bottom) to discuss and agree on the data
requirements and the processes involved
– Design
– Implementation

63. Information Engineering Planning
phase
1. Identify Strategic Planning Factors
a. Goals
b. Critical Success factors
c. Problem Areas

64. Information Engineering Planning
phase
2. Identify Corporate Planning Objects
a. Organizational Units
b. Location
c. Business Functions
d. Entity Types

65. Information Engineering Planning
phase
3. Develop Enterprise Model
a. Functional decomposition
b. Entity- Relationship diagram
c. Planning Matrices

67. Example of process decomposition of an order fulfillment function

68. Planning matrices
• Provide an explicit approach for describing
business requirements
• Location to function (which business function
is being performed at which location)
• Unit to function (which business functions are
the responsibility of which business units)
• IS application to data entity (explains how
each information system interacts with each
data entity)

69. Planning matrices
• Supporting function to data entity (which data
are captured, used, updated, deleted within
each function)
• IS application to business objective (shows
which information systems support each
business objective)

70. Systems development life cycle (SDLC)
• Is a complete set of steps that a team of IS professionals
follow to specify, develop, maintain and replace information
systems
• Process is often viewed as a cascade of steps (see following
figure)
• Cascade or ‘waterfall’ approach as each step flows into the
next – though steps can overlap in time and it is possible to
backtrack when prior decisions need to be reconsidered

71. Database development activities during the
SDLC
Project Identification
and Selection
Project Initiation
and Planning
Analysis
Logical Design
Physical Design
Implementation
Maintenance

72. Phase 1: Project identification and
Selection:
Purpose Deliverables
• Understanding • Formal request to
Business situation conduct project
design, and
develop
information
system

73. Phase 2: Project Initiation & Planning
Purpose Deliverables
• Stating Business • Written request to
situation study the possible
• Stating how changes to existing
information system system or the
solves the problem development of a
• Stating the new system
opportunity by using
information system

74. Phase 3: Analysis
Purpose Deliverables
• Analyze Business • Functional specification
situation of system
• Determining • Meeting user
requirements requirements
• Structuring • Meeting feasibility to
requirements develop the system
• Selecting competing • Feasibility to implement
system features the system

75. Phase 4: Logical Design
Purpose Deliverables
• To elicit and Detailed functional
structure all specification of :
information a. Data
requirements b. Forma
c. Reports
d. Displays
e. Processing Rules

76. Phase 5: Physical design
Purpose Deliverables
• To develop • Computer Program
technology and • Database structures
Organizational • Technology purchase
specifications
• Physical site plans
• Organizational
redesigns

77. Phase 6: Implementation:
Purpose Deliverables
• To write programs • Programs that work
• Build data files accurately to
• Test & install new specification
system • Documentation
• Train users • Training materials
• finalize
documentation

78. Phase 7: Maintenance
Purpose Deliverables
• Monitor operations • Periodic audits to
and usefulness of check the accuracy
system of the system
• Repair and enhance
the system

79. Database development stages/ phases
1. Enterprise Modeling
2. Conceptual data modeling
3. Logical database design
4. Physical database design and definition
5. Database Implementation
6. Database maintenance

80. 1. Enterprise Modeling
• Analyze current data processing
• Analyze general functions and their database
needs
• Justify need for new data and database in
support for business

81. 2. Conceptual data modeling
• Identify scope of database requirement
• Analyze overall data requirement
• Develop preliminary conceptual data model
• Compare preliminary conceptual data model
wit enterprise data model
• Develop conceptual data model including all
entities , relationships, attributes and business
rules

82. 3: Logical database design
• Analyze- transactions, forms, displays, and
inquiries and database views.
• Integrate database views into conceptual data
model
• Identify data integrity & security
requirements
• Create stable & well defined structure for
database

83. 4. Physical database design &
definition
• Define database to DBMS
• Decide on physical organization of data
• Design database processing programs

84. 5. Database Implementation
• Code & test database processing programs
• Complete database documentation & training
materials
• Install database and convert data from prior
systems

85. 6. Database Maintenance
• Analyze database and database applications to
ensure that evolving information
requirements are met
• Tune database for improved performance
• Fix errors in database and database
applications and recover database when it is
contaminated.

86. Lets wind up…………..
• Data, Database, Database Management System
• Relationship of application programs with DBMS
• Definition of database
• Short history of database processing
• Types of database
• Components of database system
• Creating the database
• Developing databases