#xSoMoBi

Tuesday, March 12, 13

Tuesday, March 12, 13

“... software is eating the world”

Marc Andreessen - Entrepreneur/InvestorWSJ - 20AUG2011

Tuesday, March 12, 13

Tuesday, March 12, 13

“Data ... LOTS of DATA.”

Tuesday, March 12, 13

Business Intelligence is

dead

Tuesday, March 12, 13

Business Intelligence is

deadLONG LIVE

BUSINESS INTELLIGENCE!

Tuesday, March 12, 13

WELCOME TOBusiness Intelligence

2.0

Tuesday, March 12, 13

WELCOME TOBusiness Intelligence

2.0

Tuesday, March 12, 13

WELCOME TOBIG DATA

Tuesday, March 12, 13

Any information is only as good as its

________[SOURCE]

Tuesday, March 12, 13

“We have Petabytes of Clickstream data”

Tuesday, March 12, 13

...but, can you use it ?

Tuesday, March 12, 13

Even if you can, will it be #useful ?

Tuesday, March 12, 13

...wait, what IS“BIG DATA” ?

Tuesday, March 12, 13

It’s all about the context.

INFORMATION + INSIGHTS= CONTEXT

Tuesday, March 12, 13

+Tuesday, March 12, 13

RIGHT DECISIONS

INFORMATIONTIME

DEVICE=

ANYONEANYWHEREBETTERFASTER

BIG DATA

{}}Tuesday, March 12, 13

Data + Transformation

Rules + Feedback + Patterns

Information + Insights

INFORMATION

INSIGHTS

BIG DATA

$$$+ SERVICESBIG DATA

Tuesday, March 12, 13

Geo Locate the user.

Identify the IP address based on geo-location.

Designated Market Area precision.

Geofences around “hot-spots”.

#Fail

REAL WORLD EXAMPLE

Tuesday, March 12, 13

How does the “system” know - you are a Mom ?

Tuesday, March 12, 13

First we “profile” a lot of users - Behavioral Dynamics

Then we begin “associating” you with those profiles - Heuristic driven rules.

We find out that you are a “woman” - Training sets -> Increased Confidence

We then identify patterns - Clustering based data mining

HOW WE DO IT

Tuesday, March 12, 13

LIKELIHOOD OF BEING A MOM

and toy store browsing late in the afternoon.

Data from the “same user”

when they were near a school in the morning on a weekday

and when they were at a nail salon during school hours

+++

Re-affirmation of the pattern

ID’ed using Device impression

Pattern of a parent

Pattern of a female user

+++}

Tuesday, March 12, 13

BIG DATA

INTERPRETABLE UNINTERPRETABLE

INFORMATION

IRRELEVANT RELEVANT

Tuesday, March 12, 13

RELEVANT INSIGHTSIGNALNOISE

UNINTERPRETABLE

Tuesday, March 12, 13

Big Data

Velocity

Volume

Variety

Batch

Streaming Data

Zettabytes Terabytes

Unstructured Data

Structured Data

Tuesday, March 12, 13

BIG DATALANDSCAPE

Tuesday, March 12, 13

Analytics Infrastructure

Operational Infrastructure

Infrastructure Asa

Service(IAAS)

Oracle

MySQL

Structured Databases

Analytics and Visualization

Business Intelligence

Data Providers

Log Data Apps Vertical Apps

Hadoop MapReduce Apache HBASE Cassandra

BIG DATA LANDSCAPE

Tuesday, March 12, 13

DATA IN MOTION

vs.DATA AT REST

Tuesday, March 12, 13

APPLICATIONSvs.

ANALYTICS

Tuesday, March 12, 13

DATA VELOCITY vs.

JUDGEMENT CALL

Tuesday, March 12, 13

$28 billion of IT spend through 2012

2 million jobs in the tech industry by 2015

6 million across other industries.

HOW BIG IS BIG ?

Tuesday, March 12, 13

MOBILE +BIG DATA

Tuesday, March 12, 13

It’s not just about Push.

Context

Real Time analysis using time, geo-data and Social Updates

WHERE DOES MOBILE FIT IN?

Data Layer Transition is in full swing

Push Notifications via Intelligent Alerts

Tuesday, March 12, 13

User specific themes - based on memory

(usage + history)

Context

Mutual value addition to the Data

WHERE DOES MOBILE FIT IN?

INTERACTIVEPinch, Swipe, Zoom, and Drag/Drop data sources

Tuesday, March 12, 13

COEXISTENCE [SoMoBi]

60%

60%

50%

30%

Tuesday, March 12, 13

Internet of Things

M2M --> P2M

COEXISTENCE [SoMoBi]

70% abandonment rate^ what does this mean?

Tuesday, March 12, 13

VERTICALS +BIG DATA

Tuesday, March 12, 13

SALESSocial + Context + Location = $$$

Facebook + Twitter + Foursquare notifications

Identify trends that lead to poor leads + losses

Tuesday, March 12, 13

Personalized products

Interpreting network data

Minutes not Hours.

TELECOM

Tuesday, March 12, 13

Aging Infrastructure

Traffic Data, Sewer Level monitoring

High Costs of Maintenance

Fight Crime

URBAN PLANNING

Tuesday, March 12, 13

Fraud Analysis + Risk + Compliance

Copyright + IPP

“This call may be recorded for Quality Assurance and Training purposes”Sentiment Analysis and Social Media

OTHER SECTORS

Tuesday, March 12, 13

McKinsey Report on Big Data - 2012

Tuesday, March 12, 13

Predicting Unemployment

Foreclosure

$

Tuesday, March 12, 13

BIG DATABECKONS...

Tuesday, March 12, 13

“Meta”

“Big”

“Swoooooosh”

“Privacy”

“Structure”

BIG DATA IN ACTION

Tuesday, March 12, 13

Skynet’s here.

Pay for Privacy

Avoid Stalkers

76 working daysPrivacy advocates vs Company Policy

BIG DATA ADOPTION

Tuesday, March 12, 13

“BIG DATA has it’s roots in good data”Data Exhaust is no longer an excuse.

Not a replacement, but a complement.

INTEGRATION.Tuesday, March 12, 13

“BIG DATA has it’s roots in good data” - anonymous brilliant thinker(s)

Data Exhaust is no longer an excuse.

Not a replacement, but a complement.

INTEGRATION.Tuesday, March 12, 13

THANK YOU,

Tuesday, March 12, 13

04.25.2013

06.20.2013#show&tell

#mobileGAMES

(open call)

(all play & no work)Tuesday, March 12, 13