big data + mobile + social
DESCRIPTION
This presentation outlines ways that data already affects our lives, how integration with social and mobile can sometimes lead to the wrong conclusion by not taking into consideration the motivation behind the data, and how big data could potentially work to our benefit.TRANSCRIPT
#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
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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
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McKinsey Report on Big Data - 2012
Tuesday, March 12, 13
Predicting Unemployment
Foreclosure
$
Tuesday, March 12, 13
BIG DATABECKONS...
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“Meta”
“Big”
“Swoooooosh”
“Privacy”
“Structure”
BIG DATA IN ACTION
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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