GEDY126-MANAGEMENT-INFORMATION-SYSTEM-Dr.S.Saravanan.pptx

MANAGEMENT
INFORMATION SYSTEM
Dr.S.Saravanan

• Functional perspective; an information system is a technologically
implemented medium for the purpose of recording, storing, and
disseminating linguistic expressions as well as for the supporting of
inference making
• Structural perspective; an information system consists of a collection
of people, processes, data, models, technology and partly formalized
language, forming a cohesive structure which serves some
organizational purpose or function
INFORMATON SYSTEM

• Technically as a set of interrelated components that collect (or
retrieve), process, store, and distribute information to support
decision making and control in an organization

FUNCTIONS OF INFORMATION SYSTEM

1. Resources of people: (end users and IS specialists, system analyst,
programmers, data administrators etc.).
2. Hardware: (Physical computer equipments and associate device,
machines and media).
3. Software: (programs and procedures).
4. Data: (data and knowledge bases), and
5. Networks: (communications media and network support).
COMPONENTS OF A INFORMATION SYSTEM

Business intelligence refers to the technology that enables businesses
to
• organize,
• analyze and
• contextualize business data from around the company.
BI includes multiple tools and techniques to transform raw data into
meaningful and actionable information

• Data warehouse stores company information from a variety of
sources in a centralized and accessible location.
• Business analytics or data management tools mine and analyze data
in the data warehouse.
• Business performance management (BPM) tools monitor and analyze
progress towards business goals.
• A user interface (usually an interactive dashboard with data
visualization reporting tools) provides quick access the information.
PARTS OF BI SYSTEM

• Data scientists and analysts:
Analysts are BI power users, and they use centralized company data
paired with powerful analytics tools to understand where opportunities
for improvement exist and what strategic recommendations to propose
to company leadership.
• Finance:
By blending financial data with operations, marketing and sales data,
users can pull insights from which decisions can be acted upon and
understand factors that impact profit and loss.
WHERE BI IS USED?

• Marketing:
Business intelligence tools help marketers track campaign metrics from
a central digital space. BI systems can provide real-time campaign
tracking, measure each effort’s performance and plan for future
campaigns. This data gives marketing teams more visibility into overall
performance and provides contextual visuals for sharing with the
company.
• Sales:
Sales data analysts and operation managers often use BI dashboards
and key performance indicators (KPIs) for quick access to complex
information like discount analysis, customer profitability and customer
lifetime value. Sales managers monitor revenue targets, sales rep
performance along with the status of the sales pipeline using
dashboards with reports and data visualizations.
• Operations:
To save time and resources, managers can access and analyze data
like supply chain metrics to find ways to optimize processes. Business
intelligence can also ensure that service level agreements are met and
help improve distribution routes.

Analysis and Insights BI processes vast amounts of data to
forecast, budget, plan, and stay
current. Competitive analysis helps
companies understand the
competition and benchmark
competitor performance. This business
intelligence enables product and
service differentiation.
Decision-Making Support Companies gain a competitive edge
when they can leverage the existing
data at the right time to make accurate
decisions faster.
BENEFITS OF BI

Efficiency and Productivity A 360-degree view of all activities
helps companies identify issues,
improve operations, increase sales,
and in turn, increase revenue.
Customer Satisfaction BI can help you identify what services
or products you're lacking and improve
customer satisfaction by making
necessary changes. Reports help you
understand customer behavior,
develop user personas, and use real-
time data on the customer's feedback
to make corrective changes and
improve customer service and,
therefore, satisfaction.

Employee Satisfaction Using BI data, you can assess team
members' strengths and weaknesses
and assign relevant training modules
to support success. BI tools can
automatically recognize positive
behavior while regularly tracking
worker contributions and
improvement.
Savings BI insight into the corporation's raw
data will help decision-makers analyze
cost-saving opportunities like excess
inventory, human resource
redundancies, marketing overages,
too many vendors or waste in facilities
management.
Savings and Profitability BI tools can analyze any discrepancies,
inefficiencies, or errors. BI helps to
increase profit margins by providing
insights that lead to future sales and
guide where to spend future budgets.

INFORMATION SYSTEM
Classification

GEDY126-MANAGEMENT-INFORMATION-SYSTEM-Dr.S.Saravanan.pptx

• Inputs : Transactions Events
• Processing:
Validation
Sorting
Listing
Merging
Updating
Calculation
• Output:
Lists
Detail reports
Action reports
Summary reports?
Transaction Processing Systems

• Payroll systems
• Order processing systems
• Reservation systems
• Stock control systems
• Systems for payments and funds transfers
The role of TPS
• Produce information for other systems
• Cross boundaries (internal and external)
• Used by operational personnel + supervisory levels
• Efficiency oriented
Transaction processing: Examples

INPUT PROCESSING OUTPUT
Internal transactions Sorting Summary reports
Internal files Merging Action report
Structured data Summarizing Detailed reports
Management Information System

Some examples of MIS
• Sales management systems
• Inventory control systems
• Budgeting systems
• Management Reporting Systems (MRS)
• Personnel (HRM) systems
The role of MIS
• Based on internal information flows
• Support relatively structured decisions
• Inflexible and have little analytical capacity
• Used by lower and middle managerial levels
• Deals with the past and present rather than the future
• Efficiency oriented?

Internal transactions Modeling Summary reports
Internal files Simulation Forecasts
External Information? Analysis Graphs/Plots
Summarizing
DECISION SUPPORT SYSTEM

Some examples of DSS
• Group Decision Support Systems (GDSS)
• Computer Supported Co-operative work (CSCW)
• Logistics systems
• Financial Planning systems
• Spreadsheet Models?
The role of DSS
• Support ill- structured or semi-structured decisions
• Have analytical and/or modelling capacity
• Used by more senior managerial levels
• Are concerned with predicting the future
• Are effectiveness oriented?

External data Summarizing Summary reports
Internal files Simulation Forecasts
Predefined models Drilling down Graphs/plots
Executive Information System

Some examples of EIS
• Executive Information Systems tend to be highly
individualized and are often custom made for a particular
client group; however, a number of off-the-shelf EIS
packages do exist and many enterprise level systems offer
a customizable EIS module.
The role of EIS
• Are concerned with ease of use
• Are concerned with predicting the future
• Are effectiveness oriented
• Are highly flexible
• Support unstructured decisions
• Use internal and external data sources
• Used only at the most senior management levels

PERSONAL DIMENSIONS OF
INFORMATION

• TIMELINESS
• CURRENT CIRCUMSTANCES
• FREQUENCY
TIME DIMENSION

• ACCURACY
• RELEVANCE
• SCOPE
• COMPLETENESS
• CONCISENESS
LOCATION DIMENSION

• CLARITY
• DETAIL
• ORDER
• PRESENTATION
• MEDIA
FORM DIMENSION

ORGANIZATIONAL DIMENSIONS
OF INFORMATION
The Organizational Dimensions of Information includes information
flows, information granularity, and what information describes

• Information in an organization flows in four directions: up,
down, horizontally, and inward/outward
From top to bottom, the levels are:
• Strategic management, which provides an organization
with overall direction and guidance.
• Tactical management, which develops the goals and
strategies outlined by strategic management.
• Operational management, which manages and directs the
day-to-day operations and implementations of the goals
and strategies.
• Non-management employees, who actually perform daily
activities, such as order processing, developing and
producing goods and services, and serving customers.
Information flows

• The downward flow of information consists of the strategies, goals,
and directives that originate at one level and are passed to lower
levels. Many organizations are taking advantage of collaborative
technologies and systems to share and move this type of information.
• Information that flows horizontally, or the horizontal flow of
information, is between functional business units and work teams

• Outward and inward flows of information consist of information that
is communicated to customers, suppliers, distributors, and other
partners for the purpose of doing business

• Information granularity refers to the extent of detail within the information.
• On one end of this spectrum is coarse granularity, or highly summarized
information.
• At the other end is fine granularity, or information that contains a great amount
of detail.
• Peoples in the highest levels of the organization deal mainly with a coarse
granularity of information, with sales by year being an example.
• People in the lowest levels of the organization, on the other hand, need
information with fine granularity. If you consider sales again, non-management
employees need information in great detail that describes each transaction when
it occurred, whether by credit or cash… "Who made the sale, to whom that sale
was made", and so on
Information Granularity

• Internal information describes specific operational aspects of an
organization
• External information describes the environment surrounding the
organization
• Objective information quantifiably describes something that is known
• Subjective information attempts to describe something that is
unknown
What the Information describes?

IT as a key resource in
Business

• Over the years, technology has caused an explosion in commerce and
trade.
• Because of technology, many traditional business models and
concepts were revolutionized.
• Technology gave us the opportunity to see things from a new
perspective, and to approach what we were already doing from a new
perspective.
• Technology also gave us greater efficiency for conducting business.
Nessasity of IT

• Technology enables us to automate numerous processes,
which thereby increases our productivity. This is possible
because it enables us to use fewer resources, thereby
enabling us to improve on quality at a low cost and to
improve the speed with which we can deliver to
customers. In the process, it has become possible to serve
even more clients.
• Technology also makes it easy to store more information
while maintaining the integrity of that information. We
are better able to store sensitive and confidential
information in a way that makes it less vulnerable to a
data breach. The information can be retrieved instantly
when needed, and it can be analyzed not only to study
past trends but also to forecast the future. In turn, this
can help with the decision-making process.
Technology as a Source of Support and Security

• Communication is a part of business. So, transportation and
processes make business a web of complicated processes that
interplay with each other.
• With technology, it has been possible to globalize business
operations. Now, just about anyone can do business practically
anywhere, from any room in their house..
• Technology has made it possible for businesses to have a wider reach
in the world. The best example of this is the internet and the World
Wide Web. The internet is now a crucial part of any businesses’
marketing campaign, as it enables the business to attract customers
world wide.
Technology as a Link to the World

• Technology, when well-integrated with business, has
made life itself worth living.
• It would be foolish to deny, however, that there are
also threats to business brought about by technology.
These include malicious activities by activities and
organizations, such as hacking. Because of this, it is
important for businesses to exercise responsibility
when using technology to conduct business.
• With the good that technology brings, there is some
bad that must also be dealt with. All the same, it is
something that's worth all of the baggage, and we
must acknowledge and responsibly utilize it to make
our businesses better.

• Mobility is seen by many as the next great frontier for businesses.
Google’s algorithms reflect this, as they make mobile websites a
priority.
• Your business, and every aspect of it can be handled, using nothing
more than a tablet or smartphone. From content marketing to
customer relations, to sales, the back-end stuff like invoicing and
shipping , all of that power is in your hands.
• But mobile solutions aren’t just about businesses; they are also about
consumers. The millennial generation uses their phones to do
everything from buying and selling to sharing their experiences with
their friends and finding local businesses.
The Advent of Mobile Solutions

• The Phenomenon of Cloud Computing
• Increased Customer Segmentation
• Increased Connectivity
• Decreasing Costs and Increasing Utility
• A Changing Consumer Base

• Traditional competitors: Existing firms that share a firm's market space
• New market entrants: New companies have certain advantages, such as not being locked into old
equipment and high motivation, as well as disadvantages, such as less expertise and little brand recognition.
Some industries have lower barriers to entry, ie: cost less for a new company to enter the field.
• Substitute products and services: These are substitutes that your customers might use if your prices become
too high. For example, Internet telephone service can substitute for traditional telephone service. The more
substitute products and services in your industry, the less you can control pricing and raise your profit
margins.
• Customers: The power of customers grows if they can easily switch to a competitor's products and services,
or if they can force a business and its competitors to compete on price alone in a transparent marketplace
where there is little product differentiation and all prices are known instantly (such as on the Internet).
• Suppliers: The more different suppliers a firm has, the greater control it can exercise over suppliers in terms
of price, quality, and delivery schedules.
PORTER’S FIVE FORCE MODEL

• Low-cost leadership: Use information systems to achieve the
lowest operational costs and the lowest prices. For example, a
supply chain management system can incorporate an efficient
customer response system to directly link consumer behavior
to distribution and production and supply chains, helping
lower inventory and distribution costs.
• Product differentiation: Use information systems to enable
new products and services, or greatly change the customer
convenience in using your existing products and services. For
instance, Land's End uses mass customization, offering
individually tailored products or services using the same
production resources as mass production, to custom-tailor
clothing to individual customer specifications.
Generic strategies used to manage
competitive forces

• Focus on market niche: Use information systems to enable a
specific market focus and serve this narrow target market
better than competitors. Information systems support this
strategy by producing and analyzing data for finely tuned sales
and marketing techniques. Hilton Hotels uses a customer
information system with detailed data about active guests to
provide tailored services and reward profitable customers with
extra privileges and attention.
Strengthen customer and supplier intimacy: Use information
systems to tighten linkages with suppliers and develop
intimacy with customers. Chrysler Corporation uses
information systems to facilitate direct access from suppliers to
production schedules, and even permits suppliers to decide
how and when to ship suppliers to Chrysler factories. This
allows suppliers more lead time in producing goods. Strong
linkages to customers and suppliers increase switching
costs (the cost of switching from one product to a competing
product) and loyalty to your firm.

• The Internet has nearly destroyed some industries and has severely threatened more.
• The Internet has also created entirely new markets and formed the basis for thousands
of new businesses.
• Because of the Internet, the traditional competitive forces are still at work, but
competitive rivalry has become much more intense.
• Internet technology is based on universal standards, making it easy for rivals to compete
on price alone and for new competitors to enter the market.
• Because information is available to everyone, the Internet raises the bargaining power of
customers, who can quickly find the lowest-cost provider on the Web.
• Some industries, such as the travel industry and the financial services industry, have been
more impacted than others.
• However, the Internet also creates new opportunities for building brands and building
very large and loyal customer bases, such as Yahoo!, eBay, and Google.

The value chain model highlights specific activities in the business where
competitive strategies can best be applied and where information systems
are most likely to have a strategic impact. The value chain model views the
firm as a series or chain of basic activities that add a margin of value to a
firm's products or services. These activities can be categorized as either
primary activities or support activities.
• Primary activities are most directly related to the production and
distribution of the firm's products and services, which create value for the
customer. Primary activities include inbound logistics, operations,
outbound logistics, sales and marketing, and service.
• Support activities make the delivery of the primary activities possible and
consist of organization infrastructure (administration and management),
human resources (employee recruiting, hiring, and training), technology
(improving products and the production process), and procurement
(purchasing input).
VALUE CHAIN MODEL

A value web is a collection of independent firms that use information technology to coordinate their value chains to produce a product
or service for a market collectively. It is more customer-driven and operates in a less linear fashion than the traditional value chain.

• If you are sending a message or file to another person using an
application with Skype or Gmail, then you’re already using a
communications software.
• This technology, as its name implies, refers to a set of applications or
systems you can use to communicate with other people in real-time.
These apps are capable of transmitting information to each other.
COMMUNICATION SOFTWARE

• Communication software handles the day-to-day exchange of
messages among stakeholders, either internally or externally.
• Aside from that, this type of solution is also used when a remote
meeting or discussion must be had, in real-time.
• Among the most common systems in this category are live chat
platforms, messaging applications, email, VoIP, and FTPs.
• A lot of communication solutions are standalone and have features
focused on streamlining the communication aspect of businesses,
including conversations, feedback, and updates.
What does communication software do?

• Auto Receptionist
Some communication software can handle calls by themselves
without any human intervention. They act as the front-desk
receptionist that facilitates a business’s guest. They can also
forward the call to the most suitable agent available, depending
on the needs or preferences of the customer.
• Voicemail and Greetings
It allows you to record a message that will automatically play
when someone calls you, and you’re not available. Other tools
provide many custom greetings you can use for the same
purpose.
• Video Conferencing
This feature lets you conduct group video calls. It is especially
helpful to teams with members who are located miles apart
from each other. You can hold virtual meetings instead of letting
everyone travel and gather in one place.
FEATURES OF COMMUNICATION SOFTWARE

• Audio Conferencing
With this feature, you can call and talk with not just one person. It
allows many people to chat simultaneously with each other.
• Call Recording
Various communication platforms carry the capability to record
conversations, be it audio or video. This is helpful since the recorded
call is useful in various ways. For instance, you can use it as future
reference or as evidence that will help resolve disputes and issues. It’s
also ideal for training purposes or as a recap material for previous
meeting sessions

1. Live Chat
Commonly installed on websites, this type of software allows businesses to
give more personalized customer support to their current and potential
clients. It’s also the most accessible among the communication software
family as it’s usually embedded on business websites, and anyone who visits
them will be greeted by either a bot or a live agent through the chat.
Live chat is also a good analytics tool as it provides you with reports
regarding the browsing behavior of your visitors. This, in turn, can be used
to create customized support and chat experiences for customers. The
information gathered can also be used for making and managing advertising
campaigns as well.
• Examples: RumbleTalk, HelpOnClick Live Chat Software
TYPES OF COMMUNICATION SOFTWARE

2. Web Conferencing and Video Software
• Perfect for remote settings, this type of solution allows you to
conduct meetings, conferences, webinars, etc. in case the
involved personnel is unable to meet you physically. It’s also
available on various devices like desktops, laptops, tablets,
smartphones, and others. Advanced capabilities, like screen-
sharing and live document transfer, are supported as well.
• Examples: GoToMeeting, Speek, GoToWebinar
3. Unified Communications Software and Call Center Software
• This type of product is ideal for call center use. It’s also the
best communication software for companies with a large
number of telephone lines. Moreover, this type of solution is
the most comprehensive with advanced features that support
Voice over Internet Protocol (VoIP) and Private Branch
Exchange (PBX).
• Examples: Five9, Phone.com, RingCentral

• Data ownership is the act of having legal rights and complete control
over a single piece or set of data elements.
• It defines and provides information about the rightful owner of data
assets and the acquisition, use and distribution policy implemented
by the data owner.
What Does Data Ownership Mean?

• Inappropriate access to, or disclosure of, protectively marked or
personal data by staff, contractors, volunteers and the public,
whether accidental or deliberate
• Internal threat - staff, acting in error or deliberately, or external
parties accessing your information illegally and exposing it/acting
maliciously to defraud you or your customers
• Information loss - particularly during transfer or movement of
information, or as a result of business change (government or internal
restructure)
Information risks to manage

• Loss of access to information
• Loss of digital continuity - i.e. losing the ability to use your information in
the way required when needed. By use we mean being able to find, open,
work with, understand and trust your information. The lifecycle of a piece
of information - how long you need to use and keep it - is often different to
the lifecycle of the IT system used to access and support it.
• Poor quality of information and poor quality assurance, for example, of
data sets.
• Poor change management - business needs change, systems change, your
information risk appetite may change, so you need to keep your policies
and processes in step accordingly.

• Dirty data refers to data that is inaccurate, incomplete, inconsistent
,outdated or duplicate data in a database.
• Dirty data severely hurts your bottom line, wastes a lot of marketing
dollars and time
DIRTY DATA

• Duplicate data are records or entries that negligently share data with
another record in your database. The most common form of duplicate data
is a complete carbon copy of another record. These are considered to be
the worst kind of data pollution. The most typical duplicated objects are
contacts, leads, and accounts.
Duplicate data in your CRM can lead to:
Decreased ROI on CRM and marketing automation systems
Poor customer service
Biases in metrics and analytics
Poor targeting and wasted marketing effort
Inaccurate reporting and less informed decisions
DUPLICATE DATA

• Imagine you found a report which fits your project, only to later discover
that the report is outdated. So, Outdated data is basically information that
is incorrect, incomplete, or simply no longer in use.
Common ways how outdated data is accumulated:
Unwanted duplicate copies of emails
Individuals who have changed roles or companies
Old server session cookies
Web content that is no longer accurate
When organizations rebrand or get acquired
Software and systems when evolving from their previous iterations
OUTDATED DATA

• Incomplete data is the most common occurring dirty data.
• A record that lacks key fields on master data records such as industry
type, title or last names, etc. which are useful for business.
• For example, if you failed to classify your customers by industry, you
cannot target your sales and marketing initiatives by industry.
• Imagine trying to sell geolocation software to a prospect who is
located at “N/A”.
INCOMPLETE DATA

• Collecting information about your customers helps in
better understanding them and making informed
decisions to satisfy them. This can be only possible if data
is collected properly, completely, and accurately and can
also lead to costly blunders.
• Incorrect data: It occurs when the field values are
generated outside of the valid range of values. For
example, when filling a month field the range should
encompass ranges from 1 to 12, or a house or office
address should be a valid address.
• Inaccurate data: There are many instances where the data
on a field is correct but inaccurate considering the
business context. Inaccurate data can lead to costly
interruptions. For example, errors in a customer’s address
can lead to the delivery of the product at the wrong
location even though the address on which it was
delivered is correct.
INACCURATE/INCORRECT DATA

• Inconsistent data are also known as data redundancy is when the same
field value is stored in different places, which leads to inconsistency. For
example, companies have customer information on multiple systems, and
data is not kept in sync.
• The problem with inconsistent data can be explained, for example, if you
want to target all “Vice President” for an upcoming email marketing
campaign. Since ‘V.P’ ‘v.p’ ‘VP’ & ‘Vice Pres’ all mean the same thing,
however, these would only be included in the campaign if all these
variations are included in the campaign list.
• Inconsistent data hinders analytics and makes segmentation difficult when
you have to consider all variables of the same title, industry, etc.
INCONSISTENT DATA

Dirty data mainly comes from two places, systems, and people.
• Data becomes dirty in a system when errors and mistakes occur
during setup, maintenance, integrations, and duplicated fields.
• Data becomes dirty in a database when people don’t understand,
make mistakes when manually entering data, become lazy, are lacking
time, or do not have a good system for entering data.
Where does dirty data originate?

• Clean data is data that is complete, meaning there are no missing
data fields for a particular record in the database.
• Cleaning data increases efficiency, cuts costs, reduces risk and makes
the most out of your information.
• Clean data is unique, timely, valid, accurate, and consistent. When
there are no duplications in your data, your data is easily accessible
when needed, the right information is in the right place, the data is
correct, and the data is consistent when located in multiple locations
your data can be classified as clean
WHAT IS CLEAN DATA?

• Data cleaning is the process of fixing or removing incorrect,
corrupted, incorrectly formatted, duplicate, or incomplete data within
a dataset.
• When combining multiple data sources, there are many opportunities
for data to be duplicated or mislabeled. If data is incorrect, outcomes
and algorithms are unreliable, even though they may look correct.
What is data cleaning?

• Data cleaning is the process that removes data that does not belong
in your dataset.
• Data transformation is the process of converting data from one
format or structure into another. Transformation processes can also
be referred to as data wrangling, or data munging, transforming and
mapping data from one "raw" data form into another format for
warehousing and analyzing.
What is the difference between data cleaning and data
transformation?

• Remove duplicate or irrelevant observations
• Fix structural errors
• Filter unwanted outliers
• Handle missing data
• Validate
How to clean your data?

• Money Control: Money Control is a website where you can read the
latest business, financial news, Get Live Stock prices, get the financial
statements of any listed company, and much more.
• With their application, you can manage your finance with the online
Investment Portfolio. It is one of the most trusted financial websites
on the internet.
WEBSITES

• Investopedia is one of the world’s leading sources of financial content
on the web, which includes information about market news,
retirement plans, investing, comparison of financial products, and
much more.
• It is not limited to financial content, you can also find information
related to marketing concepts. Most of the time your marketing
queries are answered by Investopedia.
• The most important thing is that they have a detailed explanation of
the concepts.

• Statista is an online portal where you can find statistics, consumer
survey results, public opinion, data related to industrial sectors.
• It is one of the trusted websites for secondary data, as the data is
collected and interpreted by the top experts in the industry.
• You can find data related to more than 80,000 topics collected from
over 22,500 sources.

• Google Scholar is a freely accessible web search engine that provides
a simple way to search for scholarly literature.
• You can find research papers, articles, journals, books, conference
papers, abstracts, patents from different scholars all over the world.
• It is a wonderful resource that might be helpful while doing research
or projects.

• Spinbot is a free, automatic tool that rewrite’s the given text using
different words but gives the same meaning and saves a lot of time.
The best thing is you need not sign-up.
• This tool will help you to reduce plagiarism by changing the words.

• Google
• Microsoft Bing
• Yahoo
• Baidu
• Yandex
• DuckDuckGo
• Ask.com
• Ecosia
• Aol.com
• Internet Archive
SEARCH ENGINES

• Web 2.0, term devised to differentiate the post-
dotcom bubble World Wide Web with its emphasis
on social networking, content generated by users,
and cloud computing
• For example, when there were
few television networks, none could afford to run
programs that appealed to a limited audience, which
led to the characteristic phenomena of programming
aimed at the lowest common denominator. With the
proliferation of satellite and cable networks, however,
mass marketing began to splinter into highly refined
submarkets that cater better to individual tastes.
WEB 2.0

• Traditional brick-and-mortar bookstores could afford to stock and
display only a limited range of titles, Internet bookstores such
as Amazon discovered that total sales of niche titles actually exceed
those of mass-market best sellers. The vast quantity of niche books
makes up for the greater sales of a few popular titles—makes up, that
is, in the new digital environment of e-commerce, where counter
space is no longer limited.

• Amazon.com was also a leader in adopting user-
created content. One of the appeals to shopping at
Amazon’s site was the inclusion of amateur book
reviews, with users being able to leave personal
perspectives and interact with other reviewers. An
even more successful business example of user-
created content came from electronic games. Many
companies found that, by including simple
programming tools with their games, ordinary gamers
could create modifications, or mods, and new
scenarios that generate as much or more interest as
the original game and thereby extend its lifetime
sales.

RELATIONAL DATABASE
A relational database is a type of database that stores and provides access to
data points that are related to one another.
Relational databases are based on the relational model, an intuitive,
straightforward way of representing data in tables. In a relational database,
each row in the table is a record with a unique ID called the key. The columns
of the table hold attributes of the data, and each record usually has a value
for each attribute, making it easy to establish the relationships among data
points

• Here’s a simple example of two tables a small business might
use to process orders for its products. The first table is a
customer info table, so each record includes a customer’s
name, address, shipping and billing information, phone
number, and other contact information. Each bit of information
(each attribute) is in its own column, and the database assigns
a unique ID (a key) to each row. In the second table—a
customer order table—each record includes the ID of the
customer that placed the order, the product ordered, the
quantity, the selected size and color, and so on—but not the
customer’s name or contact information.
• These two tables have only one thing in common: the ID
column (the key). But because of that common column, the
relational database can create a relationship between the two
tables. Then, when the company’s order processing application
submits an order to the database, the database can go to the
customer order table, pull the correct information about the
product order, and use the customer ID from that table to look
up the customer’s billing and shipping information in the
customer info table. The warehouse can then pull the correct
product, the customer can receive timely delivery of the order,
and the company can get paid.

DATA MINING AND DATA
WAREHOUSING

• Data mining, the extraction of hidden predictive information from
large databases,
• The overall goal of the data mining process is to extract information
from a data set and transform it into an understandable structure for
further use
• Often Not to be confused with analytics, information extraction, or
data analysis
• But its goal is the extraction of patterns and knowledge from large
amount of data, not the extraction of data itself
DATA MINING

• It extract interesting patterns such as groups of data records(cluster
analysis), unusual records(anamoly detection)
• These patterns can then be seen as a kind of summary of the input
data, and may be used in further analysis or, for example, in machine
learning and predictive analytics
• For example, the data mining step might identify multiple groups in
the data, which can then be used to obtain more accurate prediction
results by a decision support system
DATA MINING TECHNIQUES

• Also known as an enterprise data warehouse (EDW), is a system used
for reporting and data analysis
• DWs are central repositories of integrated data from one or more
disparate sources
• Storing company data in a secondary location which is typically away
from production systems.
• Location= where information can be proactively reported and queried
against
• Goal =creation of single logical view of data that may reside in many
different physical database
DATA WAREHOUSING

• It exists to help users understand and enhance their organization's
performance
• It is designed for query and analysis rather than for transaction
processing,
• Usually contains historical data derived from transaction data, but can
include data from other sources

• Data Mart
• Online Transaction Processing
• Online Analytical Processing
TYPES OF DATA WAREHOUSING

• A data mart is a simple form of a data warehouse that is focused on
functional area such as sales, finance or marketing .
• Data marts are often built and controlled by a single department
within an organization.
• Given their single-subject focus, data marts usually draw data from
only a few sources.
• The sources could be internal operational systems, a central data
warehouse, or external data.
DATA MART

For example, the sales or finance teams can use a data mart containing sales
information only to make quarterly or yearly reports and projections

• Enable faster data access by retrieving a specific set of data for BI and
reporting. As a result, it helps accelerate business processes.
• They are easier to implement and more cost-effective than building an
enterprise data warehouse.
• Designed according to the requirements of a particular group of users
working in a specific department.
• They are comparatively more adaptable than a data warehouse. Any
change in the data model can be easily and quickly incorporated in the data
mart because of its smaller size.
• Allow granular access control rights because of extensive partitioning and
segmentation.
How Data Marts Benefit Database Management?

Dependent data marts are the subdivisions of a larger data warehouse that serves as a centralized
data source. This is something known as the top-down approach — you first create a data
warehouse and then design data marts on top of it. Within this sort of relationship, data marts do
not interact with data sources directly. Based on the subjects, different sets of data are clustered
inside a data warehouse, restructured, and loaded into respective data marts from where they can
be queried.
Dependent data marts are well suited for larger companies that need better control over the
systems, improved performance, and lower telecommunication costs.

Independent data marts act as standalone systems, meaning they can work without a
data warehouse. They receive data from external and internal data sources directly. The
data presented in independent data marts can be then used for the creation of a data
warehouse. This approach is called bottom-up.
Often, the motivation behind choosing independent data marts is shorter time to
market. They work great for small to medium-sized companies.

• Is characterized by a relatively low volume of transactions. Queries
are often very complex and involve aggregations.
• For OLAP systems, response time is an effectiveness measure.
• OLAP databases store aggregated, historical data in multi-dimensional
schemas (usually star schemas).
• OLAP systems typically have data latency of a few hours, as opposed
to data marts, where latency is expected to be closer to one day.
OLAP

OLAP (Online Analytical Processing) is the technology behind many Business Intelligence (BI) applications. OLAP
is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical
calculations, and predictive “what if” scenario (budget, forecast) planning.

• OLAP is an acronym for Online Analytical Processing. OLAP performs
multidimensional analysis of business data and provides the
capability for complex calculations, trend analysis, and sophisticated
data modeling.
• It is the foundation for many kinds of business applications for
Business Performance Management, Planning, Budgeting,
Forecasting, Financial Reporting, Analysis, Simulation Models,
Knowledge Discovery, and Data Warehouse Reporting.
• OLAP enables end-users to perform ad hoc analysis of data in multiple
dimensions, thereby providing the insight and understanding they
need for better decision making.
How is OLAP Technology Used?

• Is characterized by a large number of short on-line transactions
(INSERT, UPDATE, DELETE).
• OLTP systems emphasize very fast query processing and maintaining
data integrity in multi-access environments.
• For OLTP systems, effectiveness is measured by the number of
transactions per second.
• OLTP databases contain detailed and current data.
• The schema used to store transactional databases is the entity model
(usually 3NF)
OLTP

• OLTP systems (and the database transactions they enable) drive many
of the financial transactions we make every day, including online
banking and ATM transactions, e-commerce and in-store purchases,
and hotel and airline bookings, to name a very few. In each of these
cases, the database transaction also remains as a record of the
corresponding financial transaction.
OLTP EXAMPLES

• Process a large number of relatively simple transactions: Usually
insertions, updates, and deletions to data, as well as simple data queries
(for example, a balance check at an ATM).
• Enable multi-user access to the same data, while ensuring data
integrity: OLTP systems rely on concurrency algorithms to ensure that no
two users can change the same data at the same time and that all
transactions are carried out in the proper order. This prevents people from
using online reservation systems from double-booking the same room and
protects holders of jointly held bank accounts from accidental overdrafts.
• Emphasize very rapid processing, with response times measured in
milliseconds: The effectiveness of an OLTP system is measured by the
total number of transactions that can be carried out per second.
• Provide indexed data sets: These are used for rapid searching, retrieval,
and querying.
• Are available 24/7/365: Again, OLTP systems process huge numbers of
concurrent transactions, so any data loss or downtime can have significant
and costly repercussions. A complete data backup must be available for any
moment in time. OLTP systems require frequent regular backups and
constant incremental backups
Characteristics of OLTP systems

• OLTP is optimized for executing online database transactions. OLTP systems are
designed for use by frontline workers (e.g., cashiers, bank tellers, part desk clerks) or
for customer self-service applications (e.g., online banking, e-commerce, travel
reservations).
• OLAP, on the other hand, is optimized for conducting complex data analysis. OLAP
systems are designed for use by data scientists, business analysts, and knowledge
workers, and they support business intelligence (BI), data mining, and other decision
support applications.
OLTP VS OLAP

DAT A WAREHOUSE DATA MINING
Process of storing data in order in given
dataset
Process of finding pattern in given dataset
Data warehousing is the process of
extracting and storing data to allow easier
reporting
Data mining is the use of pattern
recognition logic to identity trends within
a sample data set and extrapolate this
information against the larger data pool
The tools in data warehousing are
designed to extract data and store it in a
method designed to provide enhanced
system performance
A typical use of data mining is to create
targeted marketing programs, identify
financial fraud
Helps in identifying the certain data in a
collection of data
Helps in figuring out a certain pattern of a
data or a cluster of data
Data mining VS Data warehousing

• A Data Warehouse Delivers Enhanced Business Intelligence : By
providing data from various sources, managers and executives will no
longer need to make business decisions based on limited data
• A Data Warehouse Saves : Time Since business users can quickly
access critical data from a number of sources—all in one place—they
can rapidly make informed decisions on key initiatives
BENEFITS OF DATA WAREHOUSING

A Data Warehouse Enhances Data Quality and
Consistency:
• Individual business units and departments including
sales, marketing, finance, and operations, will start to
utilize the same data repository as the source system
for their individual queries and reports
• Thus each of these individual business units and
departments will produce results that are consistent
with the other business units within the organization.

A Data Warehouse Provides Historical Intelligence:
• A data warehouse stores large amounts of historical
data so we can analyze different time periods and
trends in order to make future predictions
• Can enable advanced business intelligence including
time-period analysis, trend analysis, and trend
prediction

A Data Warehouse Generates a High ROI:
• Return on Investment(ROI)
• Past references shows that companies that have
implemented data warehouses have generated more
revenue and saved more money than companies that
haven’t invested on data warehouses.

User expectation
• End-user demands and expects more accurate and refined results in
return of processing,
• However the performance decreases with exploding data and so the
efficiency of the system reduces.
Systems optimization
• Business intelligence tools require frequent maintenance and fine
tuning of whole system in order to meet users' expectations.
CHALLENGES IN DATA WAREHOUSING

Data structuring
• Proper processing of data requires structuring it in a
desired format so that further operations can be
executed
• As the volume of data increases the task of
structuring the unstructured data add-on, slowing
down the processing capabilities of system and
eventually becomes hectic for the system manager to
qualify the data for analytic purpose.

Prefabricated vs. Custom warehouse
• The varieties of warehouses available in market create
ambiguity about which type to choose or go for
• Custom warehouse saves the time of building the
warehouses from various operational
• Prefabricated warehouses saves the time of initial
configuration and installation

Resource Balancing
• Many departments inside an organization tend to
access the processing capabilities of the warehouse
which eventually reduces the performance of the
system and decreases the efficiency as the stress on
the system increases.
• Access control and security are some techniques
which can be used to maintain a balance between the
utilization and performance of warehouse systems

UNIT 3
Decision Support System – Components of Decision Support System –
Geographical Information Systems - Artificial Intelligence – Expert
Systems – Neural Networks –Fuzzy Logic – Genetic Algorithms –
Intelligent Agents – Multi-Agent Systems and Agent Based Modeling

STEPS IN RATIONAL DECISION MAKING

• Objectively rational if it maximizes the value of the objective.
• Subjectively rational if it maximizes the attainment of value within
limitation of the knowledge and awareness of the subject.
• Consciously rational to the extent the process of the decision-making
is deliberate and a conscious one.
• Organizationally rational to the degree of the orientation towards the
organization.
• Personally rational to the extent it achieves an individual's personal
goals.
TYPES OF RATIONAL DECISION MAKING

• Ascertaining the problem (The main task is to define the right
problem in clear terms)
• Insufficient knowledge (For perfect rationality, total information
leading to complete knowledge is necessary)
• Not enough time to be rational (The decision maker is under
pressure to make decisions)
• The environment may not cooperate
PROBLEMS IN RATIONAL DECISION MAKING

• DSS is an interactive, flexible computer based information system.
• It uses rules and models for processing data, to support various
managerial levels, ranging from top executives to mangers, in their
decision-making.
• A DSS is usually built to support the solution of certain problem and
does not replace the decision maker. As such, it is called a DSS
application. It is user friendly with strong graphical capabilities.
INTRODUCTION TO DECISION SUPPORT
SYSTEM

COMPONENTS OF DECISION SUPPORT
SYSTEM

• Communication-driven DSS supports more than one person working
on a shared task; examples include integrated tools like Microsoft's
NetMeeting or Groove.
• Data-driven DSS or data-oriented DSS emphasizes access to and
manipulation of a time series of internal organization data and,
sometimes, external data.
• Document-driven DSS manages, retrieves, and manipulates
unstructured information in a variety of electronic formats.
• Knowledge-driven DSS provides specialized problem-solving
expertise stored as facts, rules, procedures, or in similar structures.
• Model-driven DSS emphasizes access to and manipulation of a
statistical, optimization, or simulation model. Model-driven DSS use
data and parameters provided by users to assist decision makers in
analyzing a situation; they are not necessarily data-intensive.
TYPES OF DECISION SUPPORT SYSTEM

1.Improves personal efficiency.
2.Expedites problem solving (speed up the progress of problems
solving in an organization).
3.Facilitates interpersonal communication.
4.Promotes learning or training.
5.Increases organizational control.
6.Creates a competitive advantage over competition.
7.Helps automate the managerial processes
BENEFITS OF DSS

GEOGRAPHICAL
INFORMATION SYSTEM

• A Geographic Information System (GIS) integrates hardware,
software, and data for capturing, managing, analyzing, and displaying
all forms of geographically referenced information.
• GIS allows users to view, understand, question, interpret, and
visualize data in many ways that reveal relationships, patterns, and
trends in the form of maps, globes, reports, and charts.

• GIS can combine historical customer or retail store sales data with
syndicated demographic, business, traffic, and market research data.
This dataset is then ideal for building predictive models to score new
locations or customers for sales potential, cross-selling, targeted
marketing, customer churn, and other similar applications.
• What are the business population, residential population, and
average annual income within 1 mile of a proposed site?
• Where do my best customers live?
• What competitive choices do my customers have in a given
geographical area?
GIS IN MARKETING

• GIS as a strategic tool can be used to determine which areas are not
being properly served
• GIS to help understand the profile of people who buy products and
services and thus accordingly plan how to better market the products
to consumers
• GIS technology to overlay demographic information on maps to help
identify promising new store sites, facilities

GIS for Pre Planning:
Pre planning refers to the making plans prior to the time of providing services.
For pre planning we have two major constraints they are :
• Allocation of the Resources : The First and the Foremost function of the Pre
planning is to allocate the resources efficiently. But how? So, whenever we
receive a new order we can look for our resources which are close to the location
and can reach there to load the stuffs with the optimum efficiency. So, you can do
this by using any GIS application like Google maps or any other Customized apps
created for the Logistics service provider
• Transportation Routing : Providing a service and providing effective and efficient
service both are far different having a slim line difference. That is the service is on
time , without making any defects to the products. So we can route the resources
with the help of GIS applications like maps. So maps will show you the best route,
the shortest routes from loading Location to the Delivery Location.
GIS IN LOGISTICS

• Navigation is again the way to get the routes which we have planned
before leaving for the delivery of the products to the respective
location. So GIS would be helping the Driver on route to get the
navigation according to the planned route.
• Cost Reduction/Efficiency :
GIS leads to the cost efficiency of the company as they can decide the
routes according to their choice of either having or not having the
tolls in the route, by choosing the shortest route for the
transportation. Shortest route will save time, so the another trip can
be arranged in the remaining time, fuel would be less consumed for
the shortest routes.

Fleet Management :
Fleet Management refers to the Management of the vehicle. In
logistics Fleet management refers to the Management of the
commercial vehicles. Such as – Trucks, Cars, Van, aircraft. So
management of these Vehicles includes vast functions like
financing, investing, insurance, maintenance. Driver management,
speed management, health and safety management and last but
not the least is fuel Management.
1. GPS Tracking : GPS Tracking is a useful tool for the admin and
the customers. Gone are the days when the admin used to call the
driver for getting their locations updates, but now there is no need
of calling to the driver and getting the updates. As GIS would do
that for Admin and customers, they can easily get the location of
the Vehicle in real time with the help of GPS devices which are
inbuilt in the vehicle. So this decreases the chances of be fooling
the admin or customers.
2. Vehicle finance : Vehicle finance refers to the monetary aspect
of the logistics. This includes the amount of investment in a vehicle
in the form of its maintenance, insurance, fuel etc. All these
factors make a budget for the individual trips of the vehicle. As
according to the budget they cost their customers. So Budget has
to be very specific and accurate. For making the accurate budget
GIS can help you. As you can locate your resources and can send
them according to the locations, such that you can calculate the
cost by calculating the distance and the estimated time of all the
options Available and can send the vehicle according to your
preference, that is the one which costs least.

• UPS
One of the leading parcel delivery companies, UPS, uses an AI-powered
GPS called ORION (On-road Integrated Optimisation and Navigation) to find
the fastest and most cost-efficient route for its fleet. With data submitted
by customers, drivers, and vehicles, ORION uses an algorithm to detect the
optimal route for each delivery. It is a real-time system that modifies the
routes depending on current traffic and other conditions.
• Lineage
Lineage uses AI to manage its warehouses. The algorithm predicts which
items will stay in the warehouse longer and which will leave soon. Based on
this, the items that will stay longer are stored towards the back, and the
ones that will leave quicker are kept in the front. Using this approach,
Lineage has, in fact, increased its efficiency by over 20%.
Examples

• A crucial need for AI in inventory management, other
than its ability to ensure the maintenance of stock, is its
ability to predict demand. Algorithms are now capable of
studying customer demands across vast chunks of data
and understand which items will soon be in demand and
which might fail to generate enough buzz. This is known
as ‘demand forecasting’ and is widely used across
businesses and online platforms around the world.
• An unmanned warehouse can easily be kept safe by
tracking all those who enter and leave it. Furthermore,
machines can keep track of items being put on shelves
and those leaving the warehouse by simply reading the
barcode on the package and updating inventory
accordingly.

• Machines use graph theory to predict the shipping routes that can
balance between the fastest and most cost-effective for the company.
This is especially handy for companies that service multiple customers
as shipping routes are then predicted to minimise cost while
maximising reach for as many customers as possible.
• AI can monitor supplier parameters such as cost, credit score,
quantifiable past experiences such as delivery speed, and create a list
of the best possible options for any given situation. This ensures that
a business runs smoothly and the relationship between it and its
suppliers remains effective, unbiased and cordial.

• Whenever there are people driving delivery trucks, there is a limited
amount of time they can function. Having multiple drivers on the
same route, to cater to the need of a 24×7 delivery system, is
expensive. This is where AI in logistics can prove to be a lifesaver by
automating the whole driving function. In fact, one of the largest door
to door delivery businesses in the world, Amazon, has already shown
great faith in automated delivery vehicles
• Foreign language decoder: AI customer support systems and
chatbots are also far better equipped to handle foreign customers
without a business having to go to the trouble of hiring too many
offshore support executives

EXPERT SYSTEM
Provides stored knowledge of experts to non-experts and decision
recommendations based on built-in expertise .
Expert systems are computer programmes that can reproduce the behaviour of
human experts in specific problem domains. In many places, development of
expert systems is the major focus of fifth generation software projects

• The components of an expert system are a knowledge base and
software modules that perform inferences on the knowledge and
offer answers to a user’s questions.
• Expert systems provide answers to questions in a very specific
problem area by making human like inferences about knowledge
contained in a specialized knowledge base
INTRODUCTION TO EXPERT SYSTEM

• A non-expert client seeking direct advice (ES acts as a Consultant or
Advisor)
• A student who wants to learn (ES acts as an Instructor)
• An ES builder improving or increasing the knowledge base(ES acts as a
Partner)
• An Expert (ES acts as a Colleague or an Assistant)
CLASSES OF USERS

Knowledge Base (KB): repository of special heuristics or rules
that direct the use of knowledge, facts (productions). It
contains the knowledge necessary for understanding,
formulating, & problem solving.
Working Memory(Blackboard): if forward chaining used
It describes the current problem & record intermediate results.
Records Intermediate Hypothesis & Decisions: 1. Plan, 2.
Agenda, 3. Solution
Inference Engine: the deduction system used to infer results
from user input & KB
It is the brain of the ES, the control structure(rule interpreter)
It provides methodology for reasoning
Explanation Subsystem (Justifier): Traces responsibility &
explains the ES behaviour by interactively answering question:
Why?, How?, What?, Where?, When?, Who?
User Interface: interfaces with user through Natural Language
Processing (NLP), or menus & graphics. Acts as Language
Processor for friendly, problem-oriented communication

• The loan granting decision is a combination of factors related
to an analysis of the firm's historical and proforma financial
information, qualitative information about its product market
and industry characteristics, and overall performance of the
management.
• MARBLE system captures some of these features by analysing
the economic characteristics (size, market share), financial
characteristics (profitability, liquidity, leverage), ability to repay
loans (cash flow analysis, security), value of collateral,
competitive position in industry, etc. Each of the relevant
factors is given a certain weightage to evaluate a credit risk
score.
• The evaluated credit risk score is compared with an objectively
determined standard in order to establish the credit risk
classification of the application. Based on this, the system
would recommend whether to approve the loan. If the loan is
approved, the bank establishes the terms of the loan with the
customer.
MARBLE (Managing and Recommending Business Loans Evaluations) is a loan
evaluating expert system

INTELLIGENT AGENTS
An intelligent software agent is an autonomous program that is capable
of perceiving and interpreting data sensed from its environment,
reflecting events in its environment, and taking actions to achieve given
goals without permanent guidance from its user.

• REACTIVITY: intelligent agents perceive and respond in a timely fashion to changes that occur in
their environment in order to satisfy their design objectives. The agent’s goals and/or
assumptions that form the basis for a procedure that is currently executing may be affected by a
changed environment and a different set of actions may be need to be performed.
• PRO-ACTIVENESS: reacting to an environment by mapping a stimulus into a set of responses is not
enough. As we want intelligent agents to do things for us, goal directed behavior is needed. In a
changed environment, intelligent agents have to recognize opportunities and take the initiative if
they are to produce meaningful results. The challenge to the agent designer is to integrate
effectively goal-directed and reactive behavior.
• SOCIAL ABILITY: intelligent agents are capable of interacting with other agents (and possibly
humans), through negotiation and/or cooperation, to satisfy their design objectives
An intelligent agent as one that is capable of flexible autonomous action to meet
its design objectives. Flexible means:

Other properties sometimes mentioned in the context of intelligent
agents include:
• MOBILITY: The ability to move around an electronic environment
• VERACITY: An agent will not knowingly communicate false
information
• BENEVOLENCE: Agents do not have conflicting goals and every agent
will therefore always try to do what is asked of it
• RATIONALITY: An agent will act in order to achieve its goals in so far as
its beliefs permit
• LEARNING/ADAPTATION: Agents improve performance over time

• Human-Agent: A Human-Agent use Eyes, Nose, Tongue and other
sensory organs as sensors to percept information from the
environment and uses limbs and vocal-tract as actuators to perform
an action based on the information
• Robotic Agent: Robotics Agent uses cameras and infrared radars as
sensors to record information from the Environment. It uses reflex
motors as actuators to deliver output back to the environment.
• Software Agent: Software Agents use keypad strokes, audio
commands as input sensors and display screens as actuators.
For Example– AI-based smart assistants like Siri, Alexa. They use voice
sensors to request the user’s request and search for the relevant
information in secondary sources without human intervention, and
actuators like its voice or text module relay information to the
environment.
FORMS OF INTELLIGENT AGENTS

TYPES AND RULES OF INTELLIGENT AGENTS

1. Simple Reflex Agents
They are the basic form of agents and function only in the current state. They have very
low intelligence capability as they don’t have the ability to store past state. These types
of agents respond to events based on pre-defined rules, which are pre-programmed.
They perform well only when the environment is fully observable. Thus, these agents are
helpful only in a limited number of cases, something like a smart thermostat. Simple
Reflex Agents hold a static table from where they fetch all the pre-defined rules for
acting.
2. Model-Based Agents
It is an advanced version of the Simple Reflex agent. Like Simple Reflex Agents, it can also
respond to events based on the pre-defined conditions; on top of that, it can store the
internal state (past information) based on previous events. Model-Based Agents update
the internal state at each step. These internal states aid agents in handling the partially
observable environment. To perform any action, it relies on both internal state and
current percept. However, it is almost impossible to find the exact state when dealing
with a partially observable environment.

3.Goal-Based Agents
The action taken by these agents depends on the distance from their
goal (Desired Situation). The actions are intended to reduce the
distance between the current state and the desired state. To attain
its goal, it makes use of the search and planning algorithm. One
drawback of Goal-Based Agents is that they don’t always select the
most optimized path to reach the final goal. This shortfall can be
overcome by using Utility Agent described below.
4. Utility Agents
The action taken by these agents depends on the end objective, so
they are called Utility Agents. Utility Agents are used when there are
multiple solutions to a problem, and the best possible alternative
has to be chosen. The alternative chosen is based on each state’s
utility. Then, they perform a cost-benefit analysis of each solution
and select one that can achieve the minimum cost goal.
5. Learning Agents
Learning Agents have learning abilities so that they can learn from
their past experiences. These types of agents can start from scratch
and, over time, can acquire significant knowledge from their
environment. The learning agents have four major components
which enable them to learn from their experience.

• Interface tutors: Observe user computer operations, correct user
mistakes, and provide hints and advice on efficient software use.
• Presentation Agents: Show information in a variety of reporting and
presentation forms and media based on user preferences
• Network Navigation Agents: Discover paths to information and
provide ways to view information that are preferred by a user
• Role Playing Agents: Play What-if-games and other roles to help users
understand information and make better decisions
USER INTERFACE AGENTS

• Search Agents: Help users find files and databases, search for desired
information, and suggest and find new types of information products,
media, and resources
• Information Brokers: Provide commercial services to discover and
develop information resources that fit the business or personal needs
of a user
• Information filters: Receive, find, filter discard, save, forward, and
notify users about products received or desired, including e-mail,
voice mail, and all other information media
INFORMATION MANAGEMENT AGENTS

• Fuzzy logic is currently used in a large number of processes,
such as financial analysis software, control of energy
management systems, validation of electoral processes,
medical instruments and in many other applications
The fundamental advantages of fuzzy logic are:
• 1) It allows to formalize and simulate the report of an expert in
the conduction and normalization of a process.
• 2) It provides a simple answer to the difficult modeling
procedures.
• 3) It takes into consideration several variables and its weighted
merger determines the magnitude of influence.
• 4) It continuously considers cases or exceptions of a different
nature, integrating them into the solution.
• 5) They allow the implementation of multicriteria strategies
incorporating the knowledge of the experts.
FUZZY LOGIC

• In artificial intelligence (AI) systems, fuzzy logic is used to imitate
human reasoning and cognition. Rather than strictly binary cases of
truth, fuzzy logic includes 0 and 1 as extreme cases of truth but with
various intermediate degrees of truth.
• https://www.agriculturejournals.cz/publicFiles/58223.pdf

• In automobiles, fuzzy logic is used for gear selection and is based on factors such as engine load, road conditions and style of
driving.
• In dishwashers, fuzzy logic is used to determine the washing strategy and power needed, which is based on factors such as the
number of dishes and the level of food residue on the dishes.
• In copy machines, fuzzy logic is used to adjust drum voltage based on factors such as humidity, picture density and temperature.
• In aerospace, fuzzy logic is used to manage altitude control for satellites and spacecrafts based on environmental factors.
• In medicine, fuzzy logic is used for computer-aided diagnoses, based on factors such as symptoms and medical history.
• In chemical distillation, fuzzy logic is used to control pH and temperature variables.
• In natural language processing, fuzzy logic is used to determine semantic relations between concepts represented by words and
other linguistic variables.
• In environmental control systems, such as air conditioners and heaters, fuzzy logic determines output based on factors such as
current temperature and target temperature.
• In a business rules engine, fuzzy logic may be used to streamline decision-making according to predetermined criteria.
FUZZY LOGIC APPLICATIONS

UNIT 4 - THREATS TO
INTELLECTUAL PROPERTY AND
COMPUTER CRIME
Introduction to Identity Theft – Guidelines for Ethical Computer System Usage
–Intellectual Property Threats – Cyber Crime Laws and Security Guidelines –
Precautions On Data Protection – Computer Crime – Computer Forensics –
Methods of Hiding Data Recovery and Interpretation.

IDENTITY THEFT
Identity theft occurs when someone uses your personally identifying
information, like your name, Social Security number, or credit card
number, without your permission, to commit fraud or other crimes.

What is Identity Theft?
• Identity theft" refers to crimes in which someone wrongfully obtains
and uses another person's personal data (i.e., name, date of birth,
social security number, driver's license number, and your financial
identity— credit card, bank account and phone-card numbers) in
some way that involves fraud or deception, typically for economic
gain (to obtain money or goods/services).
• Criminals also use identity theft to fraudulently obtain identification
cards, driver licenses, birth certificates, social security numbers, travel
visas and other official government papers.

How personal information can be used?
• Go on spending sprees using your credit and debit card account
numbers to buy "big-ticket" items like computers that they can easily
sell.
• Open a new credit card account, using your name, date of birth and
Aadhaar. When they use the credit card and don’t pay the bills, the
delinquent account is reported on your credit report.

• Call your credit card issuer and, pretending to be you, ask to change
the mailing address on your credit card account. The imposter then
runs up charges on your account. Because your bills are being sent to
the new address, it may take some time before you realize there’s a
problem.
• Buy cars by taking out auto loans in your name/ Education Loans

• Establish phone or wireless service in your name.
• Counterfeit checks or debit cards, and drain your bank account.
• Open a bank account in your name and write bad checks on that account.
• File for bankruptcy under your name to avoid paying debts they’ve incurred
under your name, or to avoid eviction.
• Give your name to the police during an arrest. If they’re released from police
custody, but don’t show up for their court date, an arrest warrant is issued
in your name.

How imposters get personal information?
• Business Record Theft: They get your information from businesses or
institutions by stealing files out of offices where you're a customer,
employee, patient or student; or bribing an employee who has access to
your files; or even "hacking" into the organization's computer files.
• Shoulder Surfing: A "shoulder-surfing" identity thief, standing next to you
in a checkout line, can memorize your name, address and phone number
during the short time it takes you to write a check. An identity thief can
stand near a public phone and watch you punch in your phone or credit
card numbers (or even listen in when you give your credit-card number over
the phone for a hotel room or rental-car.). In ATM center next to us.

• Dumpster Diving: They rummage through your trash, or the trash of
businesses, and landfills for personal data.
• Under the Color of Authority: They fraudulently obtain credit reports by
abusing their employer's authorized access to credit reports, or by posing
as landlords, employers or others who may have a legitimate need/right to
the information.
• Skimming: They steal your credit/debit card account numbers as your card
is processed at a restaurant, store or other business location, using a
special data collection/storage device (known as "skimmer".)

Indications of Identity Theft
• failing to receive bills or other mail, which may signal an address change by the identity thief.
• receiving credit cards, and/or statements of accounts, for which you did not apply.
• a lender tries to repossess a car you didn't know you owned.
• being contacted by the police after a crime is committed in your name.
• being denied credit for no apparent reason.
• receiving calls or letters from debt collectors or businesses about merchandise or services you did
not buy.

How to prevent Identity Theft?
• Don’t respond to unsolicited requests for personal information (your name,
birthdate, social security number, or bank account number) by phone, mail,
or online.
• Watch out for “shoulder surfers.” Shield the keypad when typing your
passwords on computers and at ATMs.
• Collect mail promptly. Ask the post office to put your mail on hold when
you are away from home for several days.
• Pay attention to your billing cycles. If bills or financial statements are late,
contact the sender.
• Review your receipts. Promptly compare receipts with account statements.
Watch for unauthorized transactions.

• Shred receipts, credit offers, account statements, and
expired cards, to prevent “dumpster divers” from getting
your personal information.
• Store personal information in a safe place at home and at
work.
• Install firewalls and virus-detection software on your
home computer.
• Create complex passwords that identity thieves cannot
guess easily. Change your passwords if a company that
you do business with has a breach of its databases
• Order your credit report once a year and review to be
certain that it doesn't include accounts that you have not
opened. Check it more frequently if you suspect someone
has gained access to your account information.

GUIDELINES FOR ETHICAL
COMPUTER USAGE

• Security is all about knowing who and what to trust
• Knowing when, and when not to, to take a person at their word
• when to trust that the person you are communicating with is indeed
the person you think you are communicating with
• when to trust that a website is or isn’t legitimate
• when to trust that the person on the phone is or isn’t legitimate
• when providing your information is or isn’t a good idea

CORPORATE SOCIAL RESPONSIBILITY
THEORIES
• Stockholder Theory
• Managers are agents of the stockholders
• Only responsible to increase profits without violating the law or fraud
• Social Contract Theory
• Responsible to all of society
• Stakeholder Theory
• Responsible to anyone affected by company

Principles of technology ethics
• Proportionality
• Good must outweigh the harm or risk
• Informed Consent
• Those affected should understand and accept risks
• Justice
• Benefits and burdens distributed fairly
• Minimized Risk
• Avoid all unnecessary risk

AITP Standards of Professional Conduct

COMPUTER CRIME
• Unauthorized use, access, modification and destruction of hardware,
software , data or network resources
• Unauthorized release of information
• Unauthorized copying of software
• Denying the end user access to his/her own hardware, software, data
or network resources
• Using or conspiring to use computer or network resources to obtain
information

Hacking & Cracking
Techniques
Internet protocol spoofing
Network packet sniffers
Denial of service attack
Social Engineering
Buffer overflow attack

Internet Protocol Spoofing
• A technique used to gain unauthorized access to computers, whereby
the intruder sends messages to a computer with an IP
address indicating that the message is coming from a trusted host. To
engage in IP spoofing, a hacker must first use a variety of techniques
to find an IP address of a trusted host and then modify
the packet headers so that it appears that the packets are coming
from that host.
• Newer routers and firewall arrangements can offer protection against
IP spoofing

NETWORK PACKET SNIFFERS
A computer program or a piece of computer hardware that can intercept and log traffic passing over a digital
network or part of a network

DENIAL OF SERVICE ATTACK
Attempt to make a machine or network unavailable to its intended users

SOCIAL ENGINEERING
Social engineering is the art of manipulating people so they give up confidential information
• Phishing
• Baiting
Baiting: These socially engineering schemes know that if you dangle something people want, many
people will take the bait.
• It can be in the form of a music or movie download on a peer-to-peer site

Phishing
It is an attempt to acquire sensitive information such as usernames,
passwords and credit card details by masquerading as a trust worthy entity
in an electronic communication.
• The message may explain there is a problem that requires you to "verify"
of information by clicking on the displayed link and providing information
in their form
• The message may notify you that you’re a ’winner’. Maybe the email
claims to be from a lottery, or a dead relative, or the millionth person to
click on their site
• The message may ask for help
• Response to a question you never had

How to recognize phishing emails?
• Spelling and bad grammar
• Links in email
• Threats
• Spoofing popular companies or websites

BUFFER OVERFLOW ATTACK
• A buffer overflow occurs when a program or process tries to store more data in
a buffer (temporary data storage area) than it was intended to hold.
• Buffers are created to contain a finite amount of data, the extra information -
which has to go somewhere - can overflow into adjacent buffers, corrupting or
overwriting the valid data held in them
• In buffer overflow attacks, the extra data may contain codes designed to trigger
specific actions, in effect sending new instructions to the attacked computer that
could, for example, damage the user's files, change data, or disclose confidential
information

CYBER THEFT
• Most involve theft of money
• “Inside jobs”
• Unauthorized activity
• Attacks through the Internet
• Most companies don’t report

Cyberterrorism
• Use IT to attack electronic infrastructure, exchange information or
make threats
• Terror related
• More political motivation than criminal
• Examples
• Shut down of government network and banks in Estonia
• Non-deliberate shut down of systems at nuclear reactor

Unauthorized Use at Work
• Time and resource theft
• Doing private consulting
• Doing personal finances
• Playing video games
• Unauthorized use of the Internet or networks
• Recreational surfing
• Racist or offensive e-mail
• Pornographic sites
• Sniffers
• Monitor network traffic or capacity
• Find evidence of improper use

Adware and Spyware
• Adware
• Useful software allows ads without consent
• Spyware
• Type of Adware
• Can steal private information
• Add advertising links to Web pages
• Redirect affiliate payments
• Change a users home page and search settings
• Make modem call premium-rate numbers
• Leave security holes that let Trojans in
• Degrade system performance
• Removal often not completely successful

How to protect from cybercrime?
• Antivirus
• Virtual private networks
• Intrusion detecting systems
• Data backup
• Annual security plan testing
• Security plan compliance audit
• Biometrics

COMPUTER FORENSICS
“Forensic computing is the process of identifying, preserving, analyzing
and presenting digital evidence in a manner that is legally
acceptable.”(Rodney Mckemmish 1999).

NEEDS OF COMPUTER FORENSICS
• To produce evidence in the court that can lead to the punishment of
the actual.
• To ensure the integrity of the computer system.
• To focus on the response to hi-tech offenses, started to intertwine
GOAL OF COMPUTER FORENSICS
The main goal of computer forensic experts is not only to find the
criminal but also to find out the evidence and the presentation of the
evidence in a manner that leads to legal action of the criminal.

DIGITAL EVIDENCE
• “Any data that is recorded or preserved on any medium in or by a
computer system or other similar device, that can be read or
understand by a person or a computer system or other similar device.
It includes a display, print out or other output of that data.”
• Latent as fingerprint or DNA
• Fragile and can be easily altered, damaged, or destroyed.
• Can be Time sensitive

TYPES OF DIGITAL EVIDENCE
1) PERSISTANT DATA, Meaning data that remains intact when the
computer is turned off. E.g. hard drives, disk drives and removable
storage devices (such as USB drives or flash drives).
2) VOLATILE DATA, Which is data that would be lost if the computer is
turned off. E.g. deleted files, computer history, the computer's registry,
temporary files and web browsing history.

RULES OF EVIDENCE
• 1) Admissible, Must be able to be used in court or elsewhere.
• 2) Authentic, Evidence relates to incident in relevant way.
• 3) Complete (no tunnel vision), Exculpatory evidence for alternative
suspects.
• 4) Reliable, No question about authenticity & veracity.
• 5) Believable, Clear, easy to understand, and believable by a jury.

LOCATIONS FOR EVIDENCE
1) Internet History Files
2) Temporary Internet Files
3) Slack/Unallocated Space
4) Buddy lists, personal chat room records, P2P, others saved areas
5) News groups/club lists/posting
6) Settings, folder structure, file names
7) File Storage Dates
8) Software/Hardware added
9) File Sharing ability
10) E-mails

Computer forensics methodogy
• 1) Shut Down the Computer
• 2) Document the Hardware Configuration of The System
• 3) Transport the Computer System to A Secure Location
• 4) Make Bit Stream Backups of Hard Disks and Floppy Disks
• 5) Mathematically Verify Data on All Storage Devices
• 6) Document the System Date and Time
• 7) Make a List of Key Search Words
• 8) Evaluate the Windows Swap File
• 9) Evaluate File Slack
• 10)Evaluate Unallocated Space (Erased Files)
• 11) Search Files, File Slack and Unallocated Space for Key Words
• 12)Document File Names, Dates and Times
• 13)Identify File, Program and Storage Anomalies
• 14)Evaluate Program Functionality
• 15)Document Your Findings

APPLICATIONS OF COMPUTER FORENSICS
• FINANCIAL FRAUD DETECTION
• CRIMINAL PROSECUTION
• CIVIL LITIGATION

UNIT 5
EMERGING TRENDS IN TECHNOLOGY FOR MANAGEMENT: Introduction
to SaaS - Cloud Computing - IT Personalization Management - VoIP -
Automatic Speech Recognition - Virtual Reality - CAVE - Biometrics -
Digital Cash - Wearable Technology – Multi – Sate CPU‘s – Holographic
Storage Devices – RFID - Ethics and Privacy Concerns in IT

SaaS
• Software as Service is a software delivery model in which software
and data are hosted centrally and accessed via web. It can be rented
• Configuration and customization-according to the customer
• Accelerated feature delivery- weekly updates
• Multi tenant architecture- single instance of the software for multiple
client organizations
• Open integration protocols- API’S and protocols for accessing
company’s internal systems

Advantages of SaaS
LOWER COST OF OWNERSHIP
• Focus on Core Competency
• Access Anywhere
• Freedom to Choose (or Better Software)
• Faster Product Cycles
• No CAPEX only OPEX
VENDOR BENEFITS:
• Increased Total Available Market
• Lower Development Costs & Quicker Time-to-Market
• Improved Customer Relationships

Applicability and types of SaaS
• Enterprise Software application:
Sharing of data between internal and external users e.g. : Salesforce CRM
application
• Single user Software application:
Runs on single user computer and serves 1 user at a time e.g. : Microsoft office
• Business Utility SaaS:
Applications like Salesforce automation are used by businesses and individuals for
managing and collecting data, streamlining collaborative processes and providing
actionable analysis. Popular use cases are Customer Relationship Management
(CRM), Human Resources and Accounting.
• Social Networking SaaS:
Applications like Facebook are used by individuals for networking and sharing
information, photos, videos, etc.

IMPORTANT FACTORS OF A GOOD SaaS
DESIGN
• Three key differentiators that separate well-designed SaaS application
from a poorly designed one
1.Scalability
2.Multi tenant efficient
3.Configurable
• Scaling the application - maximizing concurrency, and efficient use of
resources i.e. optimizing locking duration, statelessness, sharing
pooled resources such as threads and network connections, caching
reference data, and partitioning large databases

• Multi-tenancy – important architectural shift from designing isolated, single-
tenant applications
One application instance should accommodate users from multiple other
companies at the same time while providing transparency. This requires an
architecture that maximizes the sharing of resources efficiently across tenants
• Configurable - a single application instance on a single server has to
accommodate users from several different companies. Customizing the
application for one customer will change the application for other customers as
well.Traditionally customizing an application would mean changes in the
code.Each customer must use metadata to configure the way the application
appears and behaves for its users. Customers configuring applications must be
simple and easy without any extra development or operation costs

CLOUD COMPUTING
Cloud Computing refers to manipulating, configuring, and accessing the
applications online. It offers online data storage, infrastructure and application.
Cloud Computing is both a combination of software and hardware based
computing resources delivered as a network service

CHARACTERISTICS OF CLOUD COMPUTING

• IaaS Examples: Amazon Web Services (AWS), Google Compute Engine
(GCE), IBM Cloud
• PaaS Examples: Google App Engine, Windows Azure, SAP cloud
• SaaS Example: Salesforce, Microsoft office 365

ADVANTAGES OF CLOUD COMPUTING
• Lower computer costs
• Improved performance
• Reduced software costs
• Instant software updates
• Improved document format compatibility
• Unlimited storage capacity
• Increased data reliability
• Universal document access
• Latest version availability
• Easier group collaboration
• Device independence

DISADVANTAGES OF CLOUD COMPUTING
• Requires a constant Internet connection
• Does not work well with low-speed connections
• Features might be limited
• Can be slow
• Stored data can be lost
• Stored data might not be secure

ETHICS AND PRIVACY
CONCERNS IN IT

COMPUTER ETHICS
• Computer Ethics is the study of ethical issues that are associated
primarily with computing machines and the computing profession.
• Cyber ethics is the field of applied ethics that examines moral, legal,
and social issues in the development and use of cyber technology.
• Computer ethics is the analysis of the nature and social impact of
computer technology and the corresponding formulation and
justification policies for the ethical use of such technology.

CATEGORIES OF COMPUTER ETHICS
PROBLEMS
• Those ethical problems for which the computer is the instrument of
the unethical act. For example , the use of a computer to defraud the
bank.
• Those problems for which the computer is the object of the unethical
act. For example, stealing computer software and installing it on one’s
own computer to access other’s information.
• Those problems associated with the autonomous nature of
computers.

PRIVACY
• The basic right of an individual to control access to and use of
information about him/herself.
• Computers make privacy more difficult to protect, since large
amounts of data on individuals and corporations are centrally stored
on computers where an increasing number of individuals can access
it.
• Privacy invasion and illegal purposes leading to serious ethical issues
like computer abuse – hacking, cyber crimes, computer virus,
software piracy, cyber squatting and internet defamation

COMPUTER CODE OF ETHICS
• Don’t use a computer to harm other people
• Don’t interfere with other people’s computer work
• Don’t snoop around in other people’s computer files
• Don’t use a computer to steal
• Don’t use a computer to bear false witness
• Don’t copy software for which you have not paid
• Don’t use other people’s computer resources without
authorization
• Don’t appropriate other people’s intellectual output
• Think about the social consequences of the program you are
writing
• Use a computer in ways that insure consideration and respect
for your fellow humans

SECURING THE WEB
• Once your business is connected to the internet , it’s your
responsibility to protect your business data and information against
unwanted intruders.
• Sensitive information such as customer details, pricing lists and
personal records can all be stolen, corrupted or even destroyed unless
protected properly

Some issues to consider when securing your website are:
• Working procedures
• Virus and spy ware protection software
• Firewalls
• Back up data
• Using secure passwords

• An example of the basic operation behind an HDSS starts with the firing of
a blue-green argon laser.
• A beam splitter then separates the laser into two beams -- the signal beam
and the reference beam.
• The signal beam travels straight until it bounces off a mirror and into a
spatial light modulator, which is an LCD that shows pages of raw data. The
data is carried to a light-sensitive crystal.
• The reference beam emanates from the side of the beam splitter, taking a
different path to the crystal. When the two beams meet, a pattern is
created on the crystal that stores data in the volume of the crystal. Data
can be stored in different areas in the crystal.

• Holographic storage uses green lasers to write data pages containing
hundreds of kilobytes of data in the form of a hologram inside a
holographic crystal
• Holographic storage can store information in a three-dimensional (3D)
space, unlike other storage options like HDDs and flash storage, which
use a two-dimensional (2D) space, allowing data to be stored more
densely. So, more data can be stored in holographic storage in the
same space compared with HDDs

• The practical use of the storage technology for the cloud in the future
would involve developing methods that will allow for the scaling of
the storage capacity by increasing the number of partitions inside the
device while maintaining the same access rates across multiple
partitions
• The data can be accessed at much higher speeds in holographic
storage, potentially offering increased access rates because of lower
time delays

AUTOMATIC SPEECH
RECOGNITION
Automatic Speech Recognition or ASR, as it’s known in short, is the
technology that allows human beings to use their voices to speak with a
computer interface in a way that, in its most sophisticated variations,
resembles normal human conversation.

• The most advanced version of currently developed ASR technologies
revolves around what is called Natural Language Processing,
or NLP in short.
• This variant of ASR comes the closest to allowing real conversation
between people and machine intelligence and though it still has a
long way to go before reaching an apex of development, we’re
already seeing some remarkable results in the form of intelligent
smart phone interfaces like the Siri program on the iPhone and other
systems used in business and advanced technology contexts.

HOW “ASR” WORKS?
• You speak to the software via an audio feed
• The device you’re speaking to creates a wave file of your words
• The wave file is cleaned by removing background noise and normalizing volume
• The resulting filtered wave form is then broken down into what are called
phonemes. (Phonemes are the basic building block sounds of language and
words. English has 44 of them, consisting of sound blocks such as “wh”, “th”, “ka”
and “t”.
• Each phoneme is like a chain link and by analyzing them in sequence, starting
from the first phoneme, the ASR software uses statistical probability analysis to
deduce whole words and then from there, complete sentences
• Your ASR, now having “understood” your words, can respond to you in a
meaningful way.

TUNING TEST: HOW ASR LEARNS FORM
HUMAN
• Human Tuning: This is a relatively simple means of
performing ASR training. It involves human programmers
going through the conversation logs of a given ASR
software interface and looking at the commonly used
words that it had to hear but which it does not have in its
pre-programmed vocabulary. Those words are then added
to the software so that it can expand its comprehension
of speech.
• Active Learning: Active learning is the much more
sophisticated variant of ASR and is particularly being tried
with NLP versions of speech recognition technology. With
active learning, the software itself is programmed to
autonomously learn, retain and adopt new words, thus
constantly expanding its vocabulary as it’s exposed to new
ways of speaking and saying thing

SPEECH RECOGNITION SOFTWARE
• Dragon Professional
• Google Now
• Siri
• Amazon Lex
• Google Docs voice typing
• Microsoft Bing API

Practical uses of Automatic Speech
Recognition Softwares
• Voice recognition software, also called speech recognition software,
can be thought of best as intelligent transcription software.
• Most of these products will transcribe the spoken word, in real time
or from an audio file, into data or text. This information can then be
presented in the form of a document or inside of an editable text box.
• Buyers operating in the financial industry need to take into
consideration existing customer service tools as well as rules
regulating the storage and transfer of financial data

• Health care — Hospitals and clinics will use voice
recognition software to quickly collect patient information
and record clinical documentation. Medical transcription
can be offered as either a software or a service and can
save hospitals countless hours and capital on record
keeping. Transcription products intended for use in health
care take into consideration HIPAA compliance, while
generalized voice recognition tools do not.
• Law — Many law firms will employ a voice recognition
tool for the extensive bookkeeping and data entry that
comes with running a practice. These products can assist
with other activities such as task management and client
communications as well.
Voice recognition and transcription is also sometimes used
in the courtroom to record legal proceedings. In both cases,
products intended for use by legal professionals take into
consideration regulations that general voice recognition
tools don’t normally have to follow.

• Customer support — Voice recognition capability is a
popular feature within many chatbot offerings. When
a customer calls in to a customer support line, the call
usually will begin with the customer interacting with a
chatbot to narrow down their issue and route them to
the correct department. Voice recognition software is
used to collect and process a customer’s answers to
the prompted questions.
• Disability services — Since its advent, voice
recognition has been used in software and services
geared toward those with disabilities. Speech
recognition software is behind much of the closed
captioning for television and video media. Voice
recognition tools are also used by those with limited
use of their hands to transcribe their thoughts.

VIRTUAL REALITY
Virtual Reality, or VR, is the use of computer technology to create a
simulated environment which can be explored in 360 degrees. Unlike
traditional interfaces, VR places the user inside the virtual environment
to give an immersive experience

EXAMPLES OF VR
• Oculus Rift
• Samsung Gear VR
• HTC Vive
• Google Daydream View

1. Virtual Reality
• uses VR headsets or closed head-mounted displays (HMDS) to completely
insulate and transpose the user to an alternative world
2. Augmented Reality
• adds or supplements to our existing reality with digital objects and digital
object overlays
• enhances our presence by 'augmenting' reality
3. Mixed or Merged Reality
• uses holographic lens to converge VR and AR where virtual objects interact
with real-world objects

• The main difference between the two is that VR builds the
world in which we immerse ourselves through a specific
headset. It is fully immersive and everything we see is
part of an environment artificially constructed through
images, sounds, etc. On the other hand, in augmented
reality (AR), our own world becomes the framework
within which objects, images or similar are
placed. Everything we see is in a real environment and it
may not be strictly necessary to wear a headset. The
clearest and most mainstream example of this concept is
Pokémon Go.
• However, there is also a combination of both realities
called mixed reality. This hybrid technology makes it
possible, for example, to see virtual objects in the real
world and build an experience in which the physical and
the digital are practically indistinguishable.

Medicine, culture, education and architecture are some of the
areas that have already taken advantage of this technology

HOW DIGITAL CASH WORKS?
In order to use digital cash, the end user needs to open an account with a bank. They then need to ask the bank to provide
them with e-cash in lieu of their cash. For instance, the bank may deduct Rs1000 from the account and issue 1000 digital
coins of Rs1 each.
• The bank uniquely marks each coin that it issues. This is done to ensure that each coin is spent only once by a single user.
Once it is spent, it reaches a different consumer and gets a different number. This electronic marking makes the digital
cash system viable. In the absence of this marking, duplication would make the system unviable.
There are several protocols that banks have developed in order to ensure that the digital cash system works
seamlessly. Some of these protocols have been mentioned below
• Account Opening: In this case, the bank takes in cash and issues marked digital tokens
• Withdrawal: This is the opposite of the account opening. Here the electronic tokens are extinguished, and cash is provided
to the customer
• Payments: Here, digital coins are extinguished. However, the value of these coins is transferred to the counterparty. This
value may be in the form of digital coins or in the form of bank currency depending upon the customer’s preference.

• Digital money is money in purely digital form. It is not a physically
tangible asset like cash or other commodities like gold or oil.
• Digital money can streamline the current financial infrastructure,
making it cheaper and faster to conduct monetary transactions. It can
also ease monetary policy implementation by central banks.
• Examples of types of digital money are cryptocurrencies, central bank
digital currencies, and stablecoins.
• Digital money is susceptible to hacks and can compromise user
privacy.

ADVANTAGES OF DIGITAL MONEY
• Digital money eliminates the need for physical storage and safekeeping
that is a characteristic of cash-intensive systems. You do not need to invest
in a wallet or bank vaults to ensure that your money is not stolen.
• Digital money simplifies accounting and record-keeping for transactions
through technology. Therefore, manual accounting and separate entity-
specific ledgers are not necessary to maintain records of transactions.
• While it has already shortened the amount of time and the cost required to
transfer money across borders, digital money has the potential to further
revolutionize the remittance industry by eliminating intermediaries and
further reducing the costs associated with cross-border transfers.

• Digital money removes intermediaries in the implementation of
monetary policy and makes it possible to include groups of people
who were previously excluded from the economy. For example, those
who are unbanked can still participate in an economy by using digital
money present in their online wallet or mobile phones.
• In the case of cryptocurrencies, digital money transactions can
become censorship-resistant, meaning they can be impervious to
tracking by government or other authorities.

DISADVANTAGES OF DIGITAL MONEY
• Digital money is susceptible to hacking. Even as it removes the need
for physical safekeeping, digital money's origins in technology ensure
that this form of money becomes a target for hackers, who can steal
from digital wallets. A seamless financial infrastructure consisting of
digitally connected entities can be brought down by hackers. The
2018 SWIFT hacks, which affected multiple countries, are an
example. Hacks of digital money on a large scale have the potential
to bring a country's financial infrastructure to heel and become a
national security threat.
• Digital money use can compromise user privacy. Cash is anonymous,
and it is nearly impossible to track and trace its users. On the other
hand, digital money can be traced. While the use of internet cookies
enables targeted advertising, the implications for digital money
tracking are more far-reaching. For example, organizations or
governments could blacklist or freeze accounts without the
permission of users. They could also instigate double-accounting in
bank accounts, inflating expenses and reducing the overall total.

• Digital money has its own set of costs. For example, digital
wallets are required to store digital money.
Cryptocurrencies also require custody solutions that act
as a failsafe against hackers. Systems that use block
chains also have to pay transaction fees, or the costs
associated with processing the transaction, to miners.
• Digital money presents several challenges on the
governance and policy framework front. This form of
money is uncharted territory for policymakers, and
problems have already begun emerging in its ecosystem.
For example, the integrity of stablecoins is already under a
cloud after Tether, the most widely used stablecoin in
cryptocurrency markets, was found to have co-mingled
client and corporate funds and used funds from its
reserve backup – to ensure a 1:1 peg to the U.S. dollar –
to cover up its debt obligations.

The most sophisticated examples of wearable technology include AI hearing aids, Google Glass and Microsoft’s HoloLens, and
a holographic computer in the form of a VR headset. An example of a less complex form of wearable technology is a
disposable skin patch with sensors that transmit patient data wirelessly to a nearby control device.
Wearable technology is any kind of electronic device designed to be
worn on the user’s body. Such devices can take many different forms,
including jewelry, accessories, medical devices and clothing (or
elements of clothing).
The term wearable computing implies processing or communications
capabilities, but in reality, the sophistication among wearables can
vary

EXAMPLES
• Smart jewelry, such as rings, wristbands, watches and pins. Smaller devices typically
work in coordination with a smartphone app for display and interaction.
• Body-mounted sensors that monitor and transmit biological data for healthcare
purposes.
• Fitness trackers, often in the form of wristbands or straps, that monitor things like
physical activity and vital signs. Trackers may connect wirelessly to an app for data
storage, processing and reporting.
• Smart clothing with built-in technology that can perform a variety of tasks including
fitness or health monitoring, interacting with phones and other devices and
changing fabric characteristics to suit the user’s preference, activity or environment.
• Augmented reality (AR) headsets that integrate digital information into a display of
the user’s environment and mixed reality (MR) headsets that integrate physical
reality and digital content in a way that enables interaction with and among real-
world and virtual objects. (VR headsets, at the far end of the virtuality continuum,
entirely replace the user environment with digital information.)
• AI hearing aids that can filter out unwanted noises and automatically adapt for best
performance in the user’s current environment. Such devices, sometimes referred
to as hearable, can also incorporate capabilities such as fitness tracking, audio
streaming and translation.

• Currently, CPUs run in a binary-state environment, meaning that they
are solely capable of recognizing data that is represented by a
sequence of 1s and 0s. For instance, the binary equivalent of the
letter “A” is “01000001”. One of the drawbacks of binary code is that
a one character letter such as “A” has to be converted into an 8
character string in order for the computer to recognize it.
• To further illustrate this point let us take the word “binary” and
convert it into its binary equivalent of
“011000100110100101101110011000010111001001111001”.
• This increase in character string length is a major obstacle in
increasing the processing speeds of today’s computers

• Bring in the Multi-state CPU. Instead of using the traditional two
states to represent the information, they will use a number of states;
most likely ten to begin with for the numbers 0 through 9. This will
mean a major breakthrough in processing speed.
• As stated earlier, any character is represented in binary code as an
eight digit string of with each character representing two possibilities.
Therefore the number of possibilities for a string is 2x2x2x2x2x2x2x2
or 256 combinations. Compare that to a multi-state CPA, where each
character has 10 possibilities and we can attain a number of
combinations far greater than 256 in only a three character string:
10x10x10 or 1000 combinations.

• Biometrics are rising as an advanced layer to many personal and
enterprise security systems. With the unique identifiers of your
biology and behaviors, this may seem foolproof.
• Modern cybersecurity is focused on reducing the risks for this
powerful security solution: traditional passwords have long been a
point of weakness for security systems. Biometrics aims to answer
this issue by linking proof-of-identity to our bodies and behavior
patterns.

TYPES OF BIOMETRIC SECURITY
• Biological biometrics use traits at a genetic and molecular level.
These may include features like DNA or your blood, which might be
assessed through a sample of your body’s fluids.
• Morphological biometrics involve the structure of your body. More
physical traits like your eye, fingerprint, or the shape of your face can
be mapped for use with security scanners.
• Behavioral biometrics are based on patterns unique to each person.
How you walk, speak, or even type on a keyboard can be an indication
of your identity if these patterns are tracked.

EXAMPLES OF BIOMETRIC SECURITY
• Voice Recognition
• Fingerprint Scanning
• Facial Recognition
• Iris Recognition
• Heart-Rate Sensors

• Advanced biometrics are used to protect sensitive documents and
valuables. Citibank already uses voice recognition, and the British
bank Halifax is testing devices that monitor heartbeat to verify
customers' identities. Ford is even considering putting biometric
sensors in cars.
• Biometrics are incorporated in e-Passports throughout the world. In
the United States, e-passports have a chip that contains a digital
photograph of one’s face, fingerprint, or iris, as well as technology
that prevents the chip from being read — and the data skimmed —
by unauthorized data readers.

• Biometrics scanners are becoming increasingly sophisticated. You can
even find biometrics on phone security systems. For example, the
facial recognition technology on Apple's iPhone X projects 30,000
infrared dots onto a user's face to authenticate the user by pattern
matching. The chance of mistaken identity with the iPhone X
biometrics is one in a million, according to Apple.

Biometrics - Identity & Privacy Concerns
• Biometric authentication is convenient, but privacy advocates fear
that biometric security erodes personal privacy. The concern is that
personal data could be collected easily and without consent.
Biometric Data Security Concerns
• A more immediate problem is that databases of personal information
are targets for hackers. For example, when the U.S. Office of
Personnel Management was hacked in 2015, cybercriminals made off
with the fingerprints of 5.6 million government employees, leaving
them vulnerable to identity theft.

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