Real-Time Analytics in a Connected World

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1 © 2016 Teradata Real-Time Analytics in a Connected World Mo Patel Practice Director, AI & Machine Learning Advanced Analytics Center of Excellence Wharton School of Business Mack Center for Innovation Fall Conference November 11, 2016

Transcript of Real-Time Analytics in a Connected World

Page 1: Real-Time Analytics in a Connected World

1 © 2016 Teradata

Real-Time Analytics in a Connected World

Mo Patel

Practice Director, AI & Machine Learning

Advanced Analytics Center of Excellence

Wharton School of Business

Mack Center for Innovation

Fall Conference

November 11, 2016

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• What is the current state of Analytics?

• What are the driving forces of Analytics Innovation?

• What are the analytic needs of a connected consumer?

• How can we address those needs?

• What are some examples of Real-Time Analytics?

• What is next?

Agenda

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What is the current state of Analytics?

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Current State of Analytics

•Static

•Reactive

•Siloed

•Opaque

•Rules Based

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What are the driving forces of Analytics

Innovation?

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Driving Forces of Analytic Innovation: Rapid Technology Adoption

10

0

Pe

ne

tra

tio

n %

in

th

e U

.S.

12011010090807060504020 30

Internet

Airplane

Automobile

Telephone

Electricity

Mobile

Phone

PC

TV

10

100

90

80

70

60

50

40

20

30

Source: Nicholas Felton NYTimes

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Driving Forces of Analytic Innovation: Connectivity

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Driving Forces of Analytic Innovation: Self Service

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What are the analytic needs of a connected

consumer?

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Analytic Needs of a Connected Consumer

•Real-Time

•Social

•Emotional

•Immersive

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How can we address those needs?

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Connected Analytics: Machine Intelligence

Teaching Machines to learn and detect patterns from data to make future predictions

Learning Prediction Intelligence

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Connected Analytics: Real-Time Inference

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Connected Analytics: Cloud Computing

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What are some examples of Real-Time

Analytics?

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Transportation: Machine Intelligence your in-car driving coach

“Please

slow

down”

“Please be careful

switching lanes”

“You are approaching a

dangerous intersection”

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Healthcare: Real-Time Inference for better outcomes

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Retail: Real-Time Intelligence your shopping assistant

Source: Monahq.com

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Utilities/Smart Home: Predictive Intelligence your Smart Home Assistant

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What is next?

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Opportunities

• Business Model Innovation

• Online Learning & Inference

Challenges

• Privacy

• Ethics

• Liability

• Safety

• Security

What are the challenges and opportunities?

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