Presented By:
SHARIF MOHAMMADRASHED
‘Big Data’ is similar to ‘small data’, but bigger
…but having data bigger it requires different approaches: Techniques, tools and architecture
…with an aim to solve new problems …or old problems in a better way
Volume
•Data quantity
Velocity
•Data Speed
Variety
•Data Types
Veracity
•Messiness
Key enablers of appearance and growth of Big Data are
– Increase of storage capacities
– Increase of processing power
– Availability of data
– Every day we create 2.5 quintillion bytes of data; 90% of the data in the world today has been created in the last two years alone
Examining large amount of data
Appropriate information
Identification of hidden patterns, unknown correlations
Competitive advantage
Better business decisions: strategic and operational
Effective marketing, customer satisfaction, increased revenue
Applications for Big Data Analytics
Homeland Security
Finance Smarter HealthcareMulti-channel
sales
Telecom
Manufacturing
Traffic Control
Trading Analytics Fraud and Risk
Log Analysis
Search Quality
Retail: Churn, NBO
LOGO
Internet of Things
What’s the Internet of Things
Definition
(1) The Internet of Things, also called The Internet of
Objects, refers to a wireless network between objects.
(2) The term "Internet of Things" has come to describe anumber of technologies and research disciplines.
Characteristics
Event Driven
Ambient Intelligence Flexible
Structure
Semantic Sharing
Complex Access Technologies
Internet of Things
Why Internet of Things
Dynamic control of industry and daily life
Improve the resource utilization ratio
Flexible configuration.
Universal transport & internetworking
The application of IoT
Scenario: shopping
(2) When shopping in the market,
the goods will introduce themselves.
(1) When entering the doors, scanners
will identify the tags on her clothing.
(4) When paying for the goods, the
microchip of the credit card will
communicate with checkout reader.
(3) When moving the goods, the reader
will tell the staff to put a new one.
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What Is Data Mining?
Data mining: discovering interesting patterns from large amounts of data.
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Steps of Data Mining
Data integration
Data selection
Data cleaning
Data transformation
Data mining
Pattern evaluation
Knowledge presentation
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Application of Data Mining
Industry
Finance
Insurance
Telecommunication
Transport
Consumer goods
Scientific Research
Utilities
Application
Credit Card Analysis
Claims,Fraud Analysis
Call record analysis
Logistics management
Promotion analysis
Image, Video, Speech
Power usage analysis
A developed urban area that create sustainableeconomic development & high quality of life byexcelling in multiple key areas; Economic,mobility,environment,people,living & Gov. excelling inthese key areas can be done so through strong humancapital, social capital and/or ICT infrastructure.
Features
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Smart parking
Intelligent transport system
Tele-care
Traffic management
Smart grids
Smart urban lighting
Waste management
Smart city maintenance
Smart taxi
Digital-signage.
Top 10 Smart City
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o Vienna
o Toronto
o Paris
o New York
o London
o Tokyo
o Berlin
o Copenhagen
o Hong Kong
o Barcelona
Challenges
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• Small portion of ICT in new city development
• Technology changes too fast
• Too many stakeholders
In terms of infrastructure
In term of transport system
Entertainment & Education Facility
Energy efficiency & Reducing water conservation