big data
DESCRIPTION
This presentation talking something about big data.Especially,big data application and challenge ahead.TRANSCRIPT
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Big Data
Group C: Wei Luo,JunHao Min,ZhiXiang Guo
JiaQiang Dong,Hui Huang
WHUT
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What is Big Data we are a part of it every day
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What Does Big Data Look Like
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In Practice
Cloud or in-house? Big data is big Big data is messy Culture
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appdomain of big data
Internet domain Weather domain Telecommunication domain Medical domain Demographics domain Financial domain Application Which use the technology of
big data benefit to us
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Automotive Data warehouse optimization Predictive asset optimization Connected vehicle Actionable customer insight
Telecommunications active call center Smarter campaigns Network analytics Location-based services
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Banking Optimize offers and cross sell Contact center efficiency and problem
resolution Payment fraud detection and
investigation Counterparty credit risk management
Insurance Create a customer-focused enterprise Optimize enterprise risk management Optimize multi-channel interaction Increase flexibility and streamline
operations
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Consumer Products Optimized promotions effectiveness
Micro-market campaign management
Real-time demand forecast
Oil & Gas Advanced condition monitoring
Drilling surveillance & optimization
Production surveillance & optimization
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Energy and Utilities Distribution load forecasting and scheduling Create targeted customer offerings Condition-based maintenance Enable customer energy management Smart meter analytics
Government Threat prediction and prevention Social program fraud, waste and errors Tax compliance - fraud and abuse Crime prediction and prevention
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Healthcare Measure and act on population health Engage consumers in their healthcare Health monitoring and intervention
Travel & Transportation Customer analytics and loyalty marketing Capacity & pricing optimization Predictive maintenance optimization
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Technologies Machine learning Machine learning, a branch of artificial intelligence, concerns the �
construction and study of systems that can learn from data. For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages. After learning, it can then be used to classify new emailmessages into spam and non-spam folders
Tom M. Mitchell provided a widely quoted, more formal definition: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E".
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Machine learning algorithms can be organized into a taxonomy based on the desired outcome of the algorithm or the type of input available during training the machine
Technologies
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Decision tree learning A tree showing survival of
passengers on the Titanic ("sibsp" is the number of spouses or siblings aboard). The figures under the leaves show the probability of survival and the percentage of observations in the leaf.
Technologies
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Natural language processing Natural language processing (NLP) is a field of computer science artificial
intelligence and linguistics concerned with the interactions between computers and human (natural) languages 。
Technologies
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terminology
Technologies
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Cluster analysis The result of a cluster analysis shown as the coloring
of the squares into three clusters.
Technologies
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The trends of big data Rapid Growth
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The trends of big data Big Data Is The Big Opportunity
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The trends of big dataQ
ualit
y O
f Pati
ent
Care
Legacy System &Traditional Data
New System & Big Data
TreatmentPathways On
Summary Data
TreatmentPathways
OnAll The Data
Social & Economic Factors
InternationalResults
IndividualPatient History
Deliver Better Healthcare With Big Data
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Challenges ahead
Invade User's privacy Real time is a real problem The Missing Skills triangle Easy-to-use big data tools infancy
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Challenges ahead Invade User's privacy
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Real time is a real problem
Challenges ahead
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Computer Sciences
Statistics
Business
Data Sciences
Challenges ahead
The Missing Skills triangle
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Easy-to-use big data tools infancy
Challenges ahead
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Conclusions Big data is a Phenomena,is a Methodology. Big data might be a Challenge,but also is a Chance
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Thanks...