Intel IT s Big Data Transformation. Aziz Safa VP, GM Enterprise Applications & Strategy November, 2014

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Intel IT’s Big Data Transformation

Aziz Safa

VP, GM Enterprise Applications & Strategy

November, 2014

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Legal Notices

This presentation is for informational purposes only. INTEL MAKES NO WARRANTIES, EXPRESS OR IMPLIED, IN THIS SUMMARY.

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as

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Copyright © 2014, Intel Corporation. All rights reserved.

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“A strategic inflection

point is an event that

changes the way

we think and act."

Andrew Grove,

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Only the Paranoid Survive…

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Big Data is about time to value

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1st

Commercia

l Computer

Integrate

d Circuit

1 st

microprocess

or

Google

1 st

_PC

Intel®

Centrino.

Facebook

World

Wide

Web

iPhone

Tablets

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2010

2015

1951

1959

1971

1991

1997

2004

2003

2007

2010

IoT /

Wearables

2014

1983

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Harnessing the Power of Big Data

Wearable Devices

Cloud Platform

Analytics Platform

Discovery

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What’s Driving Big Data?

40%

AVERAGE

SERVER COST

2002 - 2012

2

90%

STORAGE

COST / GB

2002 - 2012

2

Lower Cost of

Compute & Storage

Volume &

Type of Data

10X

Data growth by 2016

90% unstructured

11 New Investments in

New Investments in

Tools & Services

$17B

2012

2017

33 $7B

$7B

2010

$3B

1: IDC Digital Universe Study December 2012

2: Intel Forecast

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Why are we here?

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Internet of Things x Big Data = Unprecedented Value

x

₌

THINGS

VALUE

Revenu

e

Growth

Cost

Savings

Margin

Gain

50 Billion

35 ZB

DATA

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Internet of Things x Big Data = Unprecedented Challenges

x

₌

THINGS

VALUE

Revenue

Growth

Cost

Savings

Margin

Gain

50 Billion

35 ZB

NO

SECURITY

INSIGHT

NO

PROOF

DATA

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Internet of Things x Big Data = Unprecedented Challenges

x

₌

THINGS

VALUE

Revenue

Growth

Cost

Savings

Margin

Gain

50 Billion

35 ZB

DATA

Difficult to Integrate

Legacy

Systems

One-Off Solutions

Fragmented

Offerings

Lack of Standards

Poor Security

Rising costs

Delayed insights

Waste resources

on misguided

pilots

Waste resources

on misguided

pilots

Sub-optimal hardware

Bring data to compute

Fail to show ROI

Underutilized data

Fail to scale

Fail to meet TTM

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Big Data Framework

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Industries Redefining Themselves

Analytics

Access to World Data

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Collecting A City’s Pool Tax

'The technology is going so far ahead of what people think is

possible, and there is too little discussion about community

norms

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Video

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Enable

breakthroughs

in

Parkinson

disease

research

through

Big

Data

analytics

technologies

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Intel Big data analytics platform

Researcher

physician

Patient

Analytics

Big data

cloud

Big Data Framework

• Patients are not able to

objectively evaluate their

condition

• No Objective measure of PD

(Parkinson

disease)

symptoms

• Cost of trials are in the

scales of $M and they take

several years to complete

• Very

small

number

of

patients

contribute

to

research

• Researchers can not scale to

large

number

due

to

technology limitations

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Clinical trials track



Goal – Collect controlled data and validate our algorithms by running traditional

clinical trails

Virtual clinical trial track



Goal – Collect information from large amount of patients in non controlled

manner through direct recruiting of patients by MJFF

22 Tracks

Start an application

Wear a watch

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Analytics

Out of the box analytic algorithms

Activity

recognition

characteristics

Activity

symptoms

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Descriptive

Diagnostic

Predictive

Prescriptiv

e

Sales transactions

reports

Slice & Dice

Predict customer’s

propensity to buy

Rank all customers

according to their

potential sales

volume

value

difficulty

What

happened?

Why did it

happen?

What will

happen?

How can we

make it

happen?

Optimized business processes through analytics

Adapted from Gartner

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Big Data – the take away

What we believe



Advanced Analytics applied on big data can become a

competitive advantage for corporations



The evolution of Big Data in the enterprise requires

companies to build skills in focused areas and move fast to

win

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