The document provides information about management information systems and related concepts. It defines data as raw facts and figures, and information as processed data that is meaningful to end users. It distinguishes data from information, and outlines the data-information-decision process. It also classifies different types of information systems such as transaction processing systems, management information systems, and executive information systems.

1. MANAGEMENT INFORMATION SYSTEM
DATA: data is raw facts and figures typically about both physical phenomena or
business transactions. More specifically data are objective measurement of
attributes (characteristics) of entities (such as people, place, things and events).
INFORMATION: Processed data is information. Thus we can define information as
data that have been converted into a meaningful and useful context for specific end
users.
Difference between Data and Information:
DATA INFORMATION
Data is generally disorganised and Information is properly arranged,
disintegrated in the form classified and organised.
Data is in raw form Information is in finished form
Data can not be understood or made Information can be understood or made
use of by the users used by the users
Data does not depends upon Information is based upon and derived
information from the data.

2. DATA PROCESS INFORMATION DECISION
SPECIFIC IMPLEMENTATION
ACTION

3. CLASSIFICATION OF INFORMATION SYSTEM
INFORMATION
SYSTEM
OPERATION MANAGEMENT
SUPPORT SUPPORT
SYSTEM SYSTEM
T.P.S. P.C.S. E.C.S. M.I.S. D.S.S. E.I.S.

4. T.P.S.- Transaction Process System
P.C.S.- Process Control System
E.C.S.- Enterprise Collaboration System
M.I.S.- Management Information System
D.S.S.- Decision Support System
E.I.S.- Executive Information System

5. Operation Support System
The information system which supports day to day operations at the lower level
management such as cash management, credit management, billing, invoice, selling,
purchasing, inventory management, salary and wage records, etc.
TPS (Transaction Processing System)
Transaction is a process where 2 or more parties are involved in order to exchange of 1
commodity for exchange of other. There are 2 types of processing:
a) Batch Processing
b) Real Time Processing
Batch Processing Real Time Processing
Processing does not happen then and there but Processing happens then and there.
after a stipulated period of time
It is slow process It is fast process
Provides obsolete and old information Provides most updated information
Cost effective/less costly because load is Costly because good and advance quality of
divided into batches processor is required to support the load
Less possibility of errors eg. Depositing a More prone to errors eg. When we get cash bill
cheque in a bank manually after purchasing items.

6. P.C.S. (Process Control System)
System regulating any kind of process. PCS consists of that broad category
of information system in which any kind of production process which is
physical, chemical, biological, bio-chemical, production process related to
drugs, automobiles etc. In any of these process, production is controlled with
help of information system.
E.C.S. (Enterprise Collaboration System)
ECS is that category of information system which helps in collaboration and
coordination among the various stakeholders of business using the internet
platform such as intranet and extranet, where in the basic idea is to formulate
a cross functional, multi disciplinary team in order to share assets, resources
and take GD on virtual basis overcoming the barriers related to time, cost,
infrastructural and distance.
Some ECS: mobile conferencing, video conferencing, audio
conferencing, WAP, electronic meeting system, GD, e-mail, voice mail,
extranet, e-mail, voice mail, FTP

7. MANAGEMENT SUPPORT SYSTEM
It supports critical decision taking at top level, middle level and top level
management. MSS is more specialized system.
D.S.S. (Decision Support System)
Decision means selecting the best alternative among different available
alternatives.
Intelligence Phase Identifying Problem
Design Phase Develop Alternatives
Choice Phase Selection of Best Alternative
Herbert Simon approach to Decision Making
Problem can be faced at any stage of an organisation. In this phase in order to
understand the problem you are required to apply your brain, intelligence,
various statistical data, logical ability etc., designing various alternative which
can be developed for a single problem

8. MANAGEMENT INFORMATION SYSTEM
Provide information in the form of prescribed reports and displays to
support business decision making. Eg. Sales analysis, production
performance, and cost trend reporting system.
EXECUTIVE INFORMATION SYSTEM
Provide critical information from many sources tailored to
the information needs of executives. Eg. Systems for easy
access to analyses business performance, action of
competitors and economic developments to support
strategic planning.

9. PROCESS OF GENERATING INFORMATION
Process of generating information begins with process of data
collection. There are several methods of data collection. The choice of method
has an impact on the quality of information. Some of the methods of data
collections are discussed as under:
Observation
It is a first hand knowledge by a person who is responsible for collecting data.
Example: Visit to the customer for assessing the customer complaints. A visit to
assess the accidental damage for insurance payment purpose. The main
advantage of first hand knowledge is less response bias. An accuracy of
observation will decide the response.
Experimentation
Conducting an experiment can collect the information on a specific parameter.
For example: conducting a control experiment can assess the impact of a new
fertilizer dose on the yield of a crop. Conducting a test market trial can assess
the impact of a new packaging of a product. The quality of information will be a
function of design of experiment.

10. Survey
Under this method a part (sample) of population is covered on specific
aspects for the purpose of information collection, However, the quality of the
information depends on the instruments such as questionnaire used for
collecting the information, Examples of Survey are market surveys, opinion
polls, census etc.
Subjective Estimation
In the absence of experiment, surveys, and first hand information,
expert opinion may be called to collect the information. The information may be
collected from more than one expert and in more than one round of collection
from the same expert. The multiple set of information/data can be
analyzed/processed to get the right information with minimum bias. Data
pertaining to future like alternate source of energy, the life style and food habits
of later half of 21st century are collected using subjective estimations. These
estimates are called subjective since no probability law is being used for
collecting the information.

11. Transaction Processing
Sources of data for this method are ledgers, payrolls, stock statements and
sales reports of an organization. The data collected from these sources will
require the processing to get meaningful information.
Publications
In this method, data are collected from secondary sources. The sources are
publication of financial institutions, industrial organization, universities,
consulting firm's etc. This method of data collection is less costly.
Government Agencies
Some of the state agencies in all countries publish reports about the basic
parameters of the economy and other facets of the society. For example:
Publications of Central Bank of a country, in case of India publications such as
RBI Annual Report, Report on Currency and Finance, Economic survey etc.
falls in this category. These reports are available to researchers, planners and
policy makers. In addition, these reports are also available to public. However,
this information may not be directly useful but one can make use of this
information. In fact all activities in an organization generate data.

12. Strategic Roles of Information System
A company has competitive advantage over other companies when it sustains
marketability and greater market share. The area of specialisation is above
any other company in the industry. i.e. you are ahead your competitors.
Who are you competitors?
1. Me tools
2. Substitutes
3. New entrants
Me tools: These are identical products from different companies. i.e. the have
similar types product, similar technology and similar target area. Eg.
Refrigerators from samsung and LG
Substitutes: replacement of products i.e. tea and coffee
New Entrants: who are now coming up with new product of the same category.
i.e. LG producing electronics now entering in to FMCG

13. If any firm can overcome 5 forces of business the firm is able to achieve competitive
advantage in the market
Michael Porter’s 5 forces Model
THREATS
FROM
ME TOOLS &
SUBSTITUTE
THREATS INTERNAL
FROM RIVALRY AMONG
NEW ENTRANTS FIRM’S FIRMS
COMPETITIVE
ADVANTAGE
BARGAINING POWER BARGAINING POWER
OF SUPPLIERS OF CUSTOMERS
Bargaining power of customer is due to high supply and low demand. Customer become
choosy.
Bargaining power of supplier is due to high demand and low supply. Eg. Maggi

14. STRATEGIES TO ACHIEVE COMPETITIVE ADVANTAGES
1. Cost Leadership
2. Innovation: New offer and never before
3. Differentiation: Unique product and features
4. Diversification
Related Diversification- Johnson & Johnson
Non Related Diversification-ITC
5. Strategic Alliances: Alliance means ASSOCIATION
Mergers: A& B – AB company
Acquisition/Takeover: A buys B
Joint Ventures: A&B for project. Will separate after project completes
Technology Collaboration: Technical Know how is provided by one company
to another

15. ARTIFICIAL INTELLIGENCE
Artificial Intelligence is that branch of science which deals with computer in which the
goal is to develop computer which can think, see, hear, talk and feel or in other words
developed computer which can perform functions equivalent to human intelligence.
Artificial Intelligence is multi disciplinary because it has borrowed its principles from:
• Mathematics
• Operation research
• Statistics
• Psychology
• Engineering
Application areas of Artificial Intelligence
Artificial Intelligence
Cognitive Science Natural Interface
Robotics Applications
Applications Applications

16. Cognitive Sciences Applications
Something related to cognition i.e. mental ability to solve a problem using
reasoning, learning ability.
Cognitive Science. This area of artificial intelligence is based on research in biology,
neurology, psychology, mathematics, and many allied disciplines. It focuses on
researching how the human brain works and how humans think and learn. The results
of such research in human information processing are the basis for the development
of a variety of computer-based applications in artificial intelligence.
Applications in the cognitive science area of AI include the development of expert
systems and other knowledge-based systems that add a knowledge base and some
reasoning capability to information systems. Also included are adaptive learning
systems that can modify their behaviors based on information they acquire as they
operate. Chess-playing systems are primitive examples of such applications, though
many more applications are being implemented. Fuzzy logic systems can process data
that are incomplete or ambiguous, that is, fuzzy data. Thus, they can solve
unstructured problems with incomplete knowledge by developing approximate
inferences and answers, as humans do. Neural network software can learn by
processing sample problems and their solutions. As neural nets start to recognize
patterns, they can begin to program themselves to solve such problems on their own.
Genetic algorithm software uses Darwinian (survival of the fittest), randomizing, and
other mathematics functions to simulate evolutionary processes that can generate
increasingly better solutions to problems. And intelligent agents use expert system
and other AI technologies to serve as software surrogates for a variety of end user
applications.

17. ROBOTICS:
Al, engineering, and physiology are the basic disciplines of robotics. This technology
produces robot machines with computer intelligence and computer- controlled,
humanlike physical capabilities. This area thus includes applications designed to give
robots the powers of sight, or visual perception; touch, or tactile capabilities; or skill in
handling and manipulation; locomotion, or the physical ability to move over any terrain;
and navigation, or the intelligence to properly find one’s way to a destination.
NATURAL INTERFACES:
The development of natural interfaces is considered as a major area of Al applications
and is essential to the natural use of computers by humans. For example, the
development of natural languages and speech recognition are major thrusts of this area
of AI. Being able to talk to computers and robots in conversational human languages
and have them “understand” us as easily as we understand each other is a goal of AI
research. This involves research and development in linguistics, psychology, computer
science, and other disciplines. Other natural interface research applications include the
development of multisensory devices that use a variety of body movements to operate
computers. This is related to the emerging application area of virtual reality. Virtual
reality involves using multisensory human- computer interfaces that enable human users
to experience computer-simulated objects, spaces, activities, and “worlds” as if they
actually exist.

18. Expert System
An expert system is a computer based application that
guides the performance of ill-structured tasks which usually
requires experience and expertise. Using an expert system,
a non-expert can achieve performance comparable to an
expert in that particular domain. Expert systems can be
considered as an instance of a DSS. The unique feature of
an expert system is the knowledge base, the data and
decision rules which represent the expertise.
The concept of expert systems is based on the
assumption that an expert’s knowledge can be captured in
computer storage and then applied by others when the need
arises.

19. Components of Expert System
User Interface: the user interface allows the user to enter instructions
and information to the expert system and receive information from the
expert system.
Knowledge Base: the knowledge base contains the facts that describe
the problem area, and knowledge representation techniques that
describe how the facts fit together in a logical manner.
Inference Engine: the interface engine of an expert system takes the
rules that defines how the expert processes his factual knowledge and
interprets them as appropriate. Unlike a simple program, the steps are
not sequentially determined by the programmer, but follow from the
data input and the results obtained at earlier stages in the user system
Development Engine: the development engine is used to create the
expert system. The process essentially involves building the rule set.
There are two basic approaches: programming languages and expert
system shells.

20. System
• A System is a set of individual components
linked together achieve a common goal.
• A group of interrelated components working
together towards a common goal by
accepting input thereby producing output in
an organised transformation process.
• A combination of a group of interrelate or
interacting elements that form a unified
whole.

21. System Stakeholders
System stakeholder means any person
who has an interest in an existing or
proposed information system.
Stakeholders may include technical and
non- technical workers as well as internal
and external workers.
1. System Owners: Any Information System can
have one or more owners. Usually, system
owners are the managers of the organisation.
Hence, they view an information in terms of cost
and benefits to solve problems and exploit
opportunities.

22. 2. System Analyst: System analyst is a specialist who
studies the problems and needs of an organisation to
determine how people, data, process and information
technology can best accomplish improvements for the
business. The system analyst is a unique stakeholder
because he serves as a facilitator, bridges the
communication gaps that can naturally developed between
the technical system designer and builder and non
technical owners and users.
3. System Designers: A technical experts is someone who
translates system users, business requirements and
constraints into a technical solutions. A system designer
can be a database administrator, network architect, web
architect, graphics artists, security experts and technology
specialists.

23. 4. System Builders: System builder is a technical specialist who
constructs information system and components based on the
design specifications generated by the system designers.
5. System Users: System user is a person who will use or is affected
by an information system on a regular basis. They are the person
who are involved in capturing, validating, entering and exchanging
data and information. There are broadly two categories of system
users:
a) Internal System Users: Internal system users are clerical and
service workers, technical and professional staff, supervisors,
middle managers and top managers.
b) External System Users: They are also known as remote user
(a user who is located at a distant place but needs the information).
Example of external user are customers, suppliers, partners,
employees etc.

24. SDLC (System Development Life
Cycle)
SDLC describe the various stages through
which software goes during its
development. Each SDLC stage consists
have well Defined activities and methods
to perform their job.

25. Phases of SDLC:
1. Problem Identification: The
objective of problem identification
phase is to understand the
problem. This necessitates the
need for preliminary investigation.
2. Preliminary Investigation: The
main objective of preliminary
investigation is to determine
whether the request is valid and
feasible.

26. 3. Feasibility Study: Feasibility study involves seeing
whether it is possible (feasible) to do the change in the
system or build a new one, as per the outcome of
preliminary investigation.
Types of Feasibility study:
Economical Feasibility: Study to see that whether it
will be economically feasible to go ahead with the
system development. If the benefits outweigh costs,
then the decision is made to design and implement the
new system.
Technical Feasibility: It involves studying the system
for checking that whether it will be technically feasible
to develop and implement the system.
Behavioral or Operational Feasibility: The study is
done to see that weather the users staff, do will
actually be the user of the system, and accept the new
system. It is very important that the users are covered
to use the new system.

27. 4. System Analysis: System analysis is process of
studying existing system and its environment.
Interviews, outside observation and questionnaires
are different tools used for analysis of the system.
5. System Design: System Design consists of
design activities that produce system specification
satisfying the functional requirements that were
developed in the system analysis process. Cost
and benefit analysis is also done during this
phase.

28. System Design
User Interface Data Process
Design Design Design
• Screen, Form, Data Element Program and
Report, and Structure Procedure
Dialog Design Design Design

29. 6. Coding: Coding the system involves writing
programs, the design made during the design period
are converted into actual programs.
7. Testing: Testing the system involves checking all the
modules developed, during the coding phase for their
proper functionality. Testing involves checking the
system for the result by comparing the result with the
intended output.
Testing is the quality- control measure of software
development. Testing detects errors in all the phases of
software development, discovering requirements,
design and coding errors in software.

30. There are two types of testing techniques:
Black Box Testing: Detects errors in the functional
behavior of a program.
White Box Testing: Detects errors in the internal
structure of a program.
8. Implementation: Implementation phase of SDLC
involves implementation of the system developed at
the user site. Implementation involves user training,
site preparation and file conversion.

31. 9. Maintenance: When the implementation or installation
phase is completed and user staff is adjusted then the system
evaluation and maintenance of hardware and software.
There are three types of software maintenance:
– Corrective Maintenance: Corrective maintenance is
concerned with the removal of errors discovered after
delivery of software to the customer.
For example, when the library management system was
delivered, the customer found that the software was not
displaying the names of all students who checked out books.
– Adaptive Maintenance: Adaptive Maintenance is
concerned with changes in the software due to a change
in the environment in which the software functions. For
example, a banking system showing message starting that
the memory is full, after the 1,000th entry.
Perfective Maintenance: Perfective Maintenance
implements new functional system requirements generated
by the customer. For example, after testing the banking
system, the customer realizes that the system should also
show the details of daily transactions being carried out.