unit-8 current developments · use of tv and toll-free telephones in business are not usually...
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Unit-8
Current Developments
Compiled By:
Dr. Vanita Joshi
Unit-8 Currrent Development
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Content
• E-business
• Cloud Computing
• Big data
• Wireless Sensor Network
• Data Warehousing
• Data Mining
• Green Computing
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What is E-Commerce?
• Electronic commerce or e-commerce refers to a wide range of
online business activities for products and services. It also pertains
to “any form of business transaction in which the parties interact
electronically rather than by physical exchanges or direct physical
contact.”
• Business activities running over the Internet and World Wide Web
platform
• Use of TV and toll-free telephones in business are not usually
associated with e-commerce
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What is E-Commerce? (Continue…….)
• A more complete definition is: E-commerce is the use of
electronic communications and digital information processing
technology in business transactions to create, transform, and
redefine relationships for value creation between or among
organizations, and between organizations and individuals.
• Depending on the situation, electronic data interchange (EDI)
may or may not be associated with e-commerce. EDI is used for
business-to-business transactions
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Pure Vs. Partial Electronic Commerce
–Three dimensions
• the product (service) sold [physical / digital]; • the process [physical / digital] • the delivery agent (or intermediary) [physical / digital]
–Traditional commerce
• all dimensions are physical
–Pure EC
• all dimensions are digital
–Partial EC
• all other possibilities include a mix of digital and physical dimensions
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Is e-commerce the same as e-business?
e-commerce and e-business are generally used interchangeably, but they
are the distinct concepts.
In e-commerce, information and communications technology (ICT) is
used in inter-business or inter-organizational transactions (transactions
between and among firms/organizations) and in business-to-consumer
transactions (transactions between firms/organizations and individuals).
While in e-business, on the other hand, ICT is used to enhance one’s
business. It includes any process that a business organization (either a for-
profit, governmental or non-profit entity) conducts over a computer-
mediated network.
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Three primary processes are enhanced in e-business:
1. Production processes, which include procurement, ordering and
replenishment of stocks; processing of payments; electronic links with
suppliers; and production control processes, among others.
2. Customer-focused processes, which include promotional and
marketing efforts, selling over the Internet, processing of customers’ purchase orders and payments, and customer support, among others.
3. Internal management processes, which include employee services,
training, internal information-sharing, video-conferencing, and
recruiting.
Electronic applications enhance information flow between production
and sales forces to improve sales force productivity. Workgroup
communications and electronic publishing of internal business
information are likewise made more efficient.
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Types of E-Commerce
• Business-to-Business (B 2 B) e-commerce
• Business-to-Consumer ( B 2 C) e-commerce
• Consumer-to-consumer (C 2 C) e-commerce
• Business-to-Government (B 2 G) e-commerce
• Mobile Commerce (m-commerce)
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Business-to-Business (B 2 B) e-commerce
• B2B e-commerce is simply defined as e-commerce between
companies.
• This is the type of e-commerce that deals with relationships between
and among businesses. About 80% of e-commerce is of this type.
• The B2B market has two primary components: e-frastructure and e-
markets.
• The more common B2B examples and best practice models are IBM,
Hewlett Packard (HP), Cisco and Dell. Cisco, for instance, receives
over 90% of its product orders over the Internet.
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Business-to-Consumer ( B 2 C) e-commerce
• Business-to-consumer e-commerce, or commerce between
companies and consumers.
• B2C involves customers gathering information; purchasing
physical goods or information goods and receiving products
over an electronic network.
• It is the second largest and the earliest form of e-commerce.
Its origins can be traced to online retailing (or e-tailing). Thus,
the more common B2C business models are the online retailing
companies such as Amazon.com, Drugstore.com, Beyond.com.
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Consumer-to-Consumer (C 2 C) e-commerce
• Consumer-to-consumer e-commerce or C2C is simply commerce
between private individuals or consumers.
• This type of e-commerce is characterized by the growth of
electronic marketplaces and online auctions, particularly in vertical
industries where firms/businesses can bid for what they want from
among multiple suppliers. It perhaps has the greatest potential for
developing new markets.
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This type of e-commerce comes in at least three forms:
• Auctions facilitated at a portal, such as eBay, which allows
online real-time bidding on items being sold in the Web.
•Peer-to-peer systems, such as the Napster model (a protocol for
sharing files between users used by chat forums similar to IRC)
and other file exchange and later money exchange models.
• Classified ads at portal sites such as Excite Classifieds and
eWanted (an interactive, online marketplace where buyers and
sellers can negotiate and which features “Buyer Leads & Want
Ads”).
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• Business-to-government e-commerce is generally defined as commerce between companies
and the public sector.
• It refers to the use of the Internet for public procurement, licensing procedures, and other
government-related operations.
• This kind of e-commerce has two features: first, the public sector assumes a pilot/leading role
in establishing e-commerce; and second, it is assumed that the public sector has the greatest
need for making its procurement system more effective.
• Web-based purchasing policies increase the transparency of the procurement process (and
reduces the risk of irregularities). To date, however, the size of the B2G e-commerce market as
a component of total e-commerce is insignificant, as government e-procurement systems
remain undeveloped.
Business-to-Government (B 2 G) e-commerce
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Mobile Commerce (m-commerce)
• M-commerce (mobile commerce) is the buying and selling of
goods and services through wireless technology-i.e., handheld
devices such as cellular telephones and personal digital assistants
(PDAs).
• As content delivery over wireless devices becomes faster, more
secure, and scalable.
• Industries affected by m-commerce include:
* Financial services
* Telecommunications
* Service/retail
* Information services
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Components of a typical successful E-Commerce
E-commerce does not refer merely to a firm putting up a Web site for
the purpose of selling goods to buyers over the Internet. But
number of technical as well as enabling issues have to be
considered.
A typical e-commerce transaction loop involves the following major
players and corresponding requisites:
• Seller
• Transaction Partners
• Consumers
• Business / Firm
• Government
• Internet
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Big Data Unit-8 Currrent Development
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Introduction to Big Data
What is Big Data?
What makes data, “Big” Data?
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Big Data Definition
• No single standard definition…
“Big Data” is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and
analytics to manage it and extract value and hidden
knowledge from it…
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Characteristics of Big Data:
1-Scale (Volume)
• Data Volume
• 44x increase from 2009 2020
• From 0.8 zettabytes to 35zb
• Data volume is increasing exponentially
20 Exponential increase in
collected/generated data
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Characteristics of Big Data:
2-Complexity (Varity) • Various formats, types, and structures
• Text, numerical, images, audio, video,
sequences, time series, social media
data, multi-dim arrays, etc…
• Static data vs. streaming data
• A single application can be
generating/collecting many types of
data
21 To extract knowledge all these types of
data need to linked together
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Characteristics of Big Data:
3-Speed (Velocity) • Data is begin generated fast and need to be processed fast
• Online Data Analytics
• Late decisions missing opportunities
• Examples
• E-Promotions: Based on your current location, your purchase history, what
you like send promotions right now for store next to you
• Healthcare monitoring: sensors monitoring your activities and body
any abnormal measurements require immediate reaction
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Big Data: 3V’s
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Some Make it 4V’s
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Who’s Generating Big Data
Social media and networks
(all of us are generating data) Scientific instruments
(collecting all sorts of data)
Mobile devices
(tracking all objects all the time)
Sensor technology and networks
(measuring all kinds of data)
• The progress and innovation is no longer hindered by the ability to collect data
• But, by the ability to manage, analyze, summarize, visualize, and discover
knowledge from the collected data in a timely manner and in a scalable
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The Model Has Changed…
• The Model of Generating/Consuming Data has Changed
Old Model: Few companies are generating data, all others are consuming data
New Model: all of us are generating data, and all of us are consuming data
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What’s driving Big Data
- Ad-hoc querying and reporting
- Data mining techniques
- Structured data, typical sources
- Small to mid-size datasets
- Optimizations and predictive analytics
- Complex statistical analysis
- All types of data, and many sources
- Very large datasets
- More of a real-time
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Big Data Technology
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Could Computing Unit-8 Currrent Development
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What is Cloud Computing? • Cloud Computing is a general term used to describe a new
class of network based computing that takes place over the
Internet,
• basically a step on from Utility Computing
• a collection/group of integrated and networked hardware,
software and Internet infrastructure (called a platform).
• Using the Internet for communication and transport provides
hardware, software and networking services to clients
• These platforms hide the complexity and details of the
underlying infrastructure from users and applications by
providing very simple graphical interface or API (Applications
Programming Interface).
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What is Cloud Computing?
• In addition, the platform provides on demand services, that are
always on, anywhere, anytime and any place.
• Pay for use and as needed, elastic
• scale up and down in capacity and functionalities
• The hardware and software services are available to
• general public, enterprises, corporations and businesses markets
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Cloud Summary • Cloud computing is an umbrella term used to refer to
Internet based development and services
• A number of characteristics define cloud data,
applications services and infrastructure:
• Remotely hosted: Services or data are hosted on remote
infrastructure.
• Ubiquitous: Services or data are available from anywhere.
• Commodified: The result is a utility computing model
similar to traditional that of traditional utilities, like gas and
electricity - you pay for what you would want!
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Cloud Architecture
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What is Cloud Computing
34 Adopted from: Effectively and Securely Using the Cloud Computing Paradigm by peter Mell, Tim Grance
• Shared pool of configurable computing resources
• On-demand network access
• Provisioned by the Service Provider
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Cloud Computing Characteristics
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Common Characteristics:
Low Cost Software
Virtualization Service Orientation
Advanced Security
Homogeneity
Massive Scale Resilient Computing
Geographic Distribution
Essential Characteristics:
Resource Pooling
Broad Network Access Rapid Elasticity
Measured Service
On Demand Self-Service
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Cloud Service Models
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Software as a Service (SaaS)
Platform as a Service (PaaS)
Infrastructure as a Service (IaaS)
Google App
Engine
SalesForce CRM
LotusLive
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SaaS Maturity Model
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Source: Frederick Chong and Gianpaolo Carraro, “Architectures Strategies for Catching the Long Tail”
Level 2: Configurable per
customer
Level 3: configurable &
Multi-Tenant-Efficient
Level 1: Ad-Hoc/Custom – One Instance per customer
Level 4: Scalable,
Configurable & Multi-Tenant-
Efficient
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Different Cloud Computing Layers Application Service
(SaaS)
Application Platform
Server Platform
Storage Platform Amazon S3, Dell, Apple, ...
3Tera, EC2, SliceHost,
GoGrid, RightScale, Linode
Google App Engine, Mosso,
Force.com, Engine Yard,
Facebook, Heroku, AWS
MS Live/ExchangeLabs, IBM,
Google Apps; Salesforce.com
Quicken Online, Zoho, Cisco
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Services
Application
Development
Platform
Storage
Hosting
Cloud Computing Service Layers Description
Services – Complete business services such as PayPal,
OpenID, OAuth, Google Maps, Alexa
Services
Application
Focused
Infrastructure
Focused
Application – Cloud based software that eliminates the need
for local installation such as Google Apps, Microsoft Online
Storage – Data storage or cloud based NAS such as
CTERA, iDisk, CloudNAS
Development – Software development platforms used to
build custom cloud based applications (PAAS & SAAS) such
as SalesForce
Platform – Cloud based platforms, typically provided using
virtualization, such as Amazon ECC, Sun Grid
Hosting – Physical data centers such as those run by IBM,
HP, NaviSite, etc.
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Basic Cloud
Characteristics
• The “no-need-to-know” in terms of the underlying details of infrastructure, applications interface with
the infrastructure via the APIs.
• The “flexibility and elasticity” allows these systems to scale up and down at will
• utilising the resources of all kinds
• CPU, storage, server capacity, load balancing, and databases
• The “pay as much as used and needed” type of utility computing and the “always on!, anywhere and
any place” type of network-based computing.
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Basic Cloud
Characteristics
• Cloud are transparent to users and applications, they can be
built in multiple ways
• branded products, proprietary open source, hardware or software,
or just off-the-shelf PCs.
• In general, they are built on clusters of PC servers and off-the-
shelf components plus Open Source software combined with
in-house applications and/or system software.
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Software as a Service
(SaaS) • SaaS is a model of software deployment where an
application is hosted as a service provided to
customers across the Internet.
• Saas alleviates the burden of software
maintenance/support
• but users relinquish control over software versions and
requirements.
• Terms that are used in this sphere include
• Platform as a Service (PaaS) and
• Infrastructure as a Service (IaaS)
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Cloud Taxonomy
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Cloud Storage
• Several large Web companies are now exploiting the
fact that they have data storage capacity that can be
hired out to others.
• allows data stored remotely to be temporarily cached on
desktop computers, mobile phones or other Internet-linked
devices.
• Amazon’s Elastic Compute Cloud (EC2) and Simple Storage Solution (S3) are well known examples
• Mechanical Turk
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Amazon Simple Storage Service (S3)
• Unlimited Storage.
• Pay for what you use:
• $0.20 per GByte of data transferred,
• $0.15 per GByte-Month for storage used,
• Second Life Update:
• 1TBytes, 40,000 downloads in 24 hours - $200,
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Advantages of Cloud Computing
• Lower computer costs: • You do not need a high-powered and high-priced computer to
run cloud computing's web-based applications.
• Since applications run in the cloud, not on the desktop PC, your desktop PC does not need the processing power or hard disk space demanded by traditional desktop software.
• When you are using web-based applications, your PC can be less expensive, with a smaller hard disk, less memory, more efficient processor...
• In fact, your PC in this scenario does not even need a CD or DVD drive, as no software programs have to be loaded and no document files need to be saved.
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Advantages of Cloud Computing
• Improved performance: • With few large programs hogging your computer's memory,
you will see better performance from your PC.
• Computers in a cloud computing system boot and run faster because they have fewer programs and processes loaded into memory…
• Reduced software costs: • Instead of purchasing expensive software applications, you
can get most of what you need for free-ish! • most cloud computing applications today, such as the Google Docs suite.
• better than paying for similar commercial software • which alone may be justification for switching to cloud applications.
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Advantages of Cloud Computing
• Instant software updates:
• Another advantage to cloud computing is that you are no longer faced
with choosing between obsolete software and high upgrade costs.
• When the application is web-based, updates happen automatically
• available the next time you log into the cloud.
• When you access a web-based application, you get the latest version
• without needing to pay for or download an upgrade.
• Improved document format compatibility.
• You do not have to worry about the documents you create on your
machine being compatible with other users' applications or OSes
• There are potentially no format incompatibilities when everyone is
sharing documents and applications in the cloud.
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Advantages of Cloud Computing • Unlimited storage capacity: • Cloud computing offers virtually limitless storage.
• Your computer's current 1 Tbyte hard drive is small compared to the hundreds of Pbytes available in the cloud.
• Increased data reliability: • Unlike desktop computing, in which if a hard disk crashes
and destroy all your valuable data, a computer crashing in the cloud should not affect the storage of your data. • if your personal computer crashes, all your data is still out there in the
cloud, still accessible
• In a world where few individual desktop PC users back up their data on a regular basis, cloud computing is a data-safe computing platform!
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Advantages of Cloud Computing
• Universal document access: • That is not a problem with cloud computing, because you do
not take your documents with you.
• Instead, they stay in the cloud, and you can access them whenever you have a computer and an Internet connection
• Documents are instantly available from wherever you are
• Latest version availability: • When you edit a document at home, that edited version is
what you see when you access the document at work.
• The cloud always hosts the latest version of your documents • as long as you are connected, you are not in danger of having an outdated
version
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Advantages of Cloud Computing
• Easier group collaboration:
• Sharing documents leads directly to better collaboration.
• Many users do this as it is an important advantages of cloud
computing
• multiple users can collaborate easily on documents and projects
• Device independence.
• You are no longer tethered to a single computer or network.
• Changes to computers, applications and documents follow you
through the cloud.
• Move to a portable device, and your applications and
documents are still available.
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Disadvantages of Cloud Computing
• Requires a constant Internet connection:
• Cloud computing is impossible if you cannot connect to the
Internet.
• Since you use the Internet to connect to both your
applications and documents, if you do not have an Internet
connection you cannot access anything, even your own
documents.
• A dead Internet connection means no work and in areas
where Internet connections are few or inherently unreliable,
this could be a deal-breaker.
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Disadvantages of Cloud Computing
• Does not work well with low-speed connections: • Similarly, a low-speed Internet connection, such as that
found with dial-up services, makes cloud computing painful at best and often impossible.
• Web-based applications require a lot of bandwidth to download, as do large documents.
• Features might be limited: • This situation is bound to change, but today many web-
based applications simply are not as full-featured as their desktop-based applications. • For example, you can do a lot more with Microsoft PowerPoint than
with Google Presentation's web-based offering
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Disadvantages of Cloud Computing
• Can be slow:
• Even with a fast connection, web-based applications can
sometimes be slower than accessing a similar software
program on your desktop PC.
• Everything about the program, from the interface to the
current document, has to be sent back and forth from your
computer to the computers in the cloud.
• If the cloud servers happen to be backed up at that moment,
or if the Internet is having a slow day, you would not get the
instantaneous access you might expect from desktop
applications.
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Disadvantages of Cloud Computing
• Stored data might not be secure:
• With cloud computing, all your data is stored on the cloud.
• The questions is How secure is the cloud?
• Can unauthorised users gain access to your confidential data?
• Stored data can be lost:
• Theoretically, data stored in the cloud is safe, replicated across
multiple machines.
• But on the off chance that your data goes missing, you have no
physical or local backup.
• Put simply, relying on the cloud puts you at risk if the cloud lets you
down.
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Data Warehousing Unit-8 Currrent Development
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Which are our lowest/highest margin customers ?
Who are my customers and what products are they buying?
Which customers are most likely to go to the competition ?
What impact will new products/services have on revenue and margins?
What product prom- -otions have the biggest impact on revenue?
What is the most effective distribution channel?
A producer wants to know….
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58
Data, Data everywhere
yet ... • I can’t find the data I need
• data is scattered over the network
• many versions, subtle differences
I can’t get the data I need
need an expert to get the data
I can’t understand the data I found
available data poorly documented
I can’t use the data I found
results are unexpected
data needs to be transformed from one form to other
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What is a Data Warehouse?
A single, complete and
consistent store of data
obtained from a variety of
different sources made
available to end users in a
what they can understand and
use in a business context.
[Barry Devlin]
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What are the users saying...
• Data should be integrated across
the enterprise
• Summary data has a real value to
the organization
• Historical data holds the key to
understanding data over time
• What-if capabilities are required
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What is Data Warehousing?
A process of transforming
data into information and
making it available to users
in a timely enough manner to
make a difference
[Forrester Research, April 1996]
Data
Information
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Evolution
• 60’s: Batch reports • hard to find and analyze information
• inflexible and expensive, reprogram every new request
• 70’s: Terminal-based DSS and EIS (executive information systems) • still inflexible, not integrated with desktop tools
• 80’s: Desktop data access and analysis tools • query tools, spreadsheets, GUIs
• easier to use, but only access operational databases
• 90’s: Data warehousing with integrated OLAP engines and tools
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Warehouses are Very Large
Databases 35%
30%
25%
20%
15%
10%
5%
0% 5GB
5-9GB
10-19GB 50-99GB 250-499GB
20-49GB 100-249GB 500GB-1TB
Initial
Projected 2Q96
Source: META Group, Inc.
Resp
ondents
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Very Large Data Bases
• Terabytes -- 10^12 bytes:
• Petabytes -- 10^15 bytes:
• Exabytes -- 10^18 bytes:
• Zettabytes -- 10^21 bytes:
• Zottabytes -- 10^24 bytes:
Walmart -- 24 Terabytes
Geographic Information Systems
National Medical Records
Weather images
Intelligence Agency Videos
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Data Warehousing -
It is a process
• Technique for assembling and
managing data from various sources
for the purpose of answering business
questions. Thus making decisions that
were not previous possible
• A decision support database
maintained separately from the
organization’s operational database
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Data Warehouse
• A data warehouse is a
• subject-oriented
• integrated
• time-varying
• non-volatile
collection of data that is used primarily in
organizational decision making.
-- Bill Inmon, Building the Data Warehouse 1996
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Data Mining Unit-8 Currrent Development
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Data mining
• Process of semi-automatically analyzing large databases to
find patterns that are:
• valid: hold on new data with some certainty
• novel: non-obvious to the system
• useful: should be possible to act on the item
• understandable: humans should be able to interpret the pattern
• Also known as Knowledge Discovery in Databases (KDD)
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Why Data Mining • Credit ratings/targeted marketing:
• Given a database of 100,000 names, which persons are the least likely to default on their credit cards?
• Identify likely responders to sales promotions
• Fraud detection
• Which types of transactions are likely to be fraudulent, given the demographics and transactional history of a particular customer?
• Customer relationship management:
• Which of my customers are likely to be the most loyal, and which are most likely to leave for a competitor? :
Data Mining helps extract such information 73
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Applications • Banking: loan/credit card approval • predict good customers based on old customers
• Customer relationship management: • identify those who are likely to leave for a competitor.
• Targeted marketing: • identify likely responders to promotions
• Fraud detection: telecommunications, financial transactions • from an online stream of event identify fraudulent events
• Manufacturing and production: • automatically adjust knobs when process parameter changes
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Applications (continued)
• Medicine: disease outcome, effectiveness of treatments • analyze patient disease history: find relationship
between diseases
• Molecular/Pharmaceutical: identify new drugs
• Scientific data analysis: • identify new galaxies by searching for sub clusters
• Web site/store design and promotion: • find affinity of visitor to pages and modify layout
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The KDD process
• Problem fomulation
• Data collection
• subset data: sampling might hurt if highly skewed data
• feature selection: principal component analysis, heuristic search
• Pre-processing: cleaning
• name/address cleaning, different meanings (annual, yearly), duplicate removal, supplying missing values
• Transformation:
• map complex objects e.g. time series data to features e.g. frequency
• Choosing mining task and mining method:
• Result evaluation and Visualization:
Knowledge discovery is an iterative process
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Relationship with other fields
• Overlaps with machine learning, statistics, artificial
intelligence, databases, visualization but more stress
on
• scalability of number of features and instances
• stress on algorithms and architectures whereas foundations
of methods and formulations provided by statistics and
machine learning.
• automation for handling large, heterogeneous data
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Some basic operations
• Predictive:
• Regression
• Classification
• Collaborative Filtering
• Descriptive:
• Clustering / similarity matching
• Association rules and variants
• Deviation detection
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Data Mining in
Practice
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Application Areas
Industry Application
Finance Credit Card Analysis
Insurance Claims, Fraud Analysis
Telecommunication Call record analysis
Transport Logistics management
Consumer goods Promotion analysis
Data Service providers Value added data
Utilities Power usage analysis
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Why Now? • Data is being produced
• Data is being warehoused
• The computing power is available
• The computing power is affordable
• The competitive pressures are strong
• Commercial products are available
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Data Mining works with
Warehouse Data
• Data Warehousing provides the
Enterprise with a memory
ÑData Mining provides the Enterprise with intelligence
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Usage scenarios
• Data warehouse mining: • assimilate data from operational sources
• mine static data
• Mining log data
• Continuous mining: example in process control
• Stages in mining: • data selection pre-processing: cleaning
transformation mining result evaluation visualization
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Mining market
• Around 20 to 30 mining tool vendors • Major tool players: • Clementine, • IBM’s Intelligent Miner, • SGI’s MineSet, • SAS’s Enterprise Miner.
• All pretty much the same set of tools • Many embedded products: • fraud detection: • electronic commerce applications, • health care, • customer relationship management: Epiphany
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Green Computing Unit-8 Currrent Development
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Green Computing
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The positive (or least negative) relationship between the
physical computer and its impact to the environments in
which it moves through from cradle to grave
Cradle to Grave Approach
• Full life-cycle analysis, not just the product on our desks
• Looks at:
• Manufacturing
• Use during lifetime
• Disposal and reallocation
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Green Computing • Why • computer energy is often wasteful • leaving the computer on when not in use (CPU and fan consume power,
screen savers consume power)
• printing is often wasteful • how many of you print out your emails or meeting agendas
• printing out partial drafts
• for a “paperless” society, we tend to use more paper today than before computer-prevalence
• pollution • manufacturing techniques
• packaging
• disposal of computers and components
• toxicity • as we will see, there are toxic chemicals used in the manufacturing of
computers and components which can enter the food chain and water! 87
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Energy Use of PCs • CPU uses 120 Watts
• CRT uses 150 Watts • 8 hours of usage, 5 days a week = 562 KWatts • if the computer is left on all the time without proper power saver
modes, this can lead to 1,600 KWatts
• for a large institution, say a university of 40,000 students and faculty, the power bill for just computers can come to $2 million / year
• Energy use comes from • electrical current to run the CPU, motherboard, memory
• running the fan and spinning the disk(s)
• monitor (CRTs consume more power than any other computer component)
• printers
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Chemical Elements Found in Computers and Components
• Elements in bulk: lead, tin, copper, silicon, carbon, iron and aluminum
• Elements in small amounts: cadmium and mercury
• Elements in trace amounts: • germanium, gallium, barium, nickel, tantalum, indium, vanadium, terbium,
beryllium, gold, europium, titanium, ruthenium, cobalt, palladium, manganese, silver, antimony, bismuth, selenium, niobium, yttrium, rhodium, platinum, arsenic, lithium, boron, americium
• List of examples of devices containing these elements • almost all electronics contain lead & tin (as solder) and copper (as wire &
PCB tracks), though the use of lead-free solder is now spreading rapidly
• lead: solder, CRT monitors (Lead in glass), Lead-acid battery
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List Continued
• List of examples of devices containing these elements • tin: solder
• copper: copper wire, printed circuit board tracks
• aluminum: nearly all electronic goods using more than a few watts of power
• iron: steel chassis, cases & fixings
• silicon: glass, transistors, ICs, Printed circuit boards.
• nickel & cadmium: nickel-cadmium rechargeable batteries
• lithium: lithium-ion battery
• zinc: plating for steel parts
• gold: connector plating, primarily in computer equipment
• mercury: fluorescent tubes (numerous applications), tilt switches (pinball games, mechanical doorbells)
• sulphur: lead-acid battery
• carbon: steel, plastics, resistors
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Disposal • Reuse: donate your computer components to people who
may not have or have lesser quality computers • inner city schools, churches, libraries, third world countries • this however leads to the older computers being dumped but there is
probably no way around this as eventually the older computers would be discarded anyway
• Refurbish: rather than discarding your computer when the next generation is released, just get a new CPU and memory chips – upgrade rather than replace • while you will still be discarded some components, you will
retain most of the computer system (e.g., monitor, the system unit housing, cables)
• Are there adequate incentives to do either of the above? Do computer companies encourage refurbishing/upgrading?
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One More Solution: Recycling
• If companies can recycle the plastics and other
components, this can greatly reduce waste and toxins
• however, the hazardous materials in e-waste can harm the
recycle workers if they are not properly protected
• in undeveloped countries, a lot of the recycling chores are left up to
unprotected children!
• Developed countries now have facilities for recycling e-
waste
• however, in Europe, the plastics are discarded instead of
recycled because the flame retardant chemicals are too toxic to
work with
• To resolve these problems, the computer manufacturers
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How Do the Companies Rate? • 8: Nokia - regained its top position for eliminating the
worst chemicals from many products
• still needs to report on its recycling rate percentage
• 7.3: Dell - still among the top but loses points for not
having models free of the worst chemicals
• strong support for global take back
• 7.3: Lenovo - dropping down the rank for not having a
clear global take back program
• still missing out on products free of the worst chemicals on the
market
• 7: Sony Ericsson - among the top with clear timeline to
have products free of the worst chemicals by 2008
• need better chemicals take back reporting program
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Continued
• 6.7: Samsung - strong position for having a good chemical policy, but still lack products that are free from the worst chemicals • its take back system is not yet global and need improvement
• 6.7: Motorola - some products on the market are free from the worst chemicals but loses points for not providing clear timelines for eliminating these chemicals in all products • score points on reporting the recycling rate
• 6: Toshiba - good improvement particularly on waste and take back criteria • moved forward for providing some models without the worst
chemicals and for timelines for complete phase out
• 6: Fujitsu-Siemens - some models free of worst chemicals, but loses point for a weak take back and recycling program
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Continued • 5.7: Acer - standing still with improved chemical policies but no
models free of the worst chemicals • needs to improve on take back program
• 5.3: Apple - top mover with concrete timelines to eliminate the worst chemicals • loses points for not have a green product on the market and for a weak take
back program
• 5.3: HP - a free-faller, dropping down for failing to provide clear timelines for eliminating the worst chemicals • it looses points for weak definition of take back policies
• 5: Panasonic - moving up for making available products free of the worst chemicals • loses point for poor take back program
• 4: Sony - at the bottom of the rank for losing penalty point for inconsistent take back policies • some models without the worst chemicals
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Wireless Sensor Network Unit-8 Currrent Development
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Introduction-WSN • Wireless Sensor Networks are networks that
consists of sensors which are distributed in an ad hoc manner.
• These sensors work with each other to sense some physical phenomenon and then the information gathered is processed to get relevant results.
• Wireless sensor networks consists of protocols and algorithms with self-organizing capabilities.
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Example of WSN
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Comparison with ad hoc
networks
• Wireless sensor networks mainly use broadcast communication
while ad hoc networks use point-to-point communication.
• Unlike ad hoc networks wireless sensor networks are limited by
sensors limited power, energy and computational capability.
• Sensor nodes may not have global ID because of the large
amount of overhead and large number of sensors.
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Applications of Wireless Sensor
networks
The applications can be divided in three categories:
1. Monitoring of objects.
2. Monitoring of an area.
3. Monitoring of both area and objects.
* Classification due to Culler, Estrin, Srivastava
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Monitoring Area
• Environmental and Habitat Monitoring
• Precision Agriculture
• Indoor Climate Control
• Military Surveillance
• Treaty Verification
• Intelligent Alarms
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Example: Precision
Agriculture
• Precision agriculture aims at making cultural operations more efficient, while reducing
environmental impact. • The information collected from
sensors is used to evaluate optimum sowing density, estimate fertilizers and other inputs needs, and to more accurately predict crop yields.
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Monitoring Objects
• Structural Monitoring
• Eco-physiology
• Condition-based Maintenance
• Medical Diagnostics
• Urban terrain mapping
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Example: Condition-based
Maintenance
• Intel fabrication plants
• Sensors collect vibration data, monitor wear and
tear; report data in real-time
• Reduces need for a team of engineers; cutting costs
by several orders of magnitude
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Monitoring Interactions between Objects and
Space
• Wildlife Habitats
• Disaster Management
• Emergency Response
• Ubiquitous Computing
• Asset Tracking
• Health Care
• Manufacturing Process Flows
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Example: Habitat
Monitoring
• The ZebraNet Project
Collar-mounted sensors monitor zebra movement in
Kenya
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Characteristics of Wireless
Sensor Networks • Wireless Sensor Networks mainly consists of sensors.
Sensors are -
• low power
• limited memory
• energy constrained due to their small size.
• Wireless networks can also be deployed in extreme environmental conditions and may be prone to enemy attacks.
• Although deployed in an ad hoc manner they need to be self organized and self healing and can face constant reconfiguration.
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Design Challenges
• Heterogeneity
• The devices deployed maybe of various types and need to
collaborate with each other.
• Distributed Processing
• The algorithms need to be centralized as the processing is
carried out on different nodes.
• Low Bandwidth Communication
• The data should be transferred efficiently between sensors
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Continued..
• Large Scale Coordination
• The sensors need to coordinate with each other to produce required results.
• Utilization of Sensors
• The sensors should be utilized in a ways that produce the maximum performance and use less energy.
• Real Time Computation
• The computation should be done quickly as new data is always being generated.
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Operational Challenges of Wireless
Sensor Networks
• Energy Efficiency
• Limited storage and computation
• Low bandwidth and high error rates
• Errors are common • Wireless communication
• Noisy measurements
• Node failure are expected
• Scalability to a large number of sensor nodes
• Survivability in harsh environments
• Experiments are time- and space-intensive
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Enabling Technologies
Embedded Networked
Sensing
Control system w/
Small form factor
Untethered nodes
Exploit
collaborative
Sensing, action
Tightly coupled to physical world
Embed numerous distributed
devices to monitor and interact
with physical world
Network devices to coordinate and
perform higher-level tasks
Exploit spatially and temporally dense, in situ, sensing and actuation 111
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Future of WSN Smart Home / Smart Office
• Sensors controlling
appliances and electrical
devices in the house.
• Better lighting and
heating in office
buildings.
• The Pentagon building
has used sensors
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Biomedical / Medical
• Health Monitors
• Glucose
• Heart rate
• Cancer detection
• Chronic Diseases
• Artificial retina
• Cochlear implants
• Hospital Sensors
• Monitor vital signs
• Record anomalies 113
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Industrial & Commercial
• Numerous industrial and commercial applications:
• Agricultural Crop Conditions
• Inventory Tracking
• In-Process Parts Tracking
• Automated Problem Reporting
• RFID – Theft Deterrent and Customer Tracing
• Plant Equipment Maintenance Monitoring
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Traffic Management & Monitoring
Future cars could use wireless sensors to:
Handle Accidents
Handle Thefts
Sensors embedded in the roads to:
–Monitor traffic flows
–Provide real-time route updates
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