The document discusses big data and strategies for utilizing it. It notes that the value of big data lies in the personal services that are created using the large amounts of data being generated. Some key points made include: - The amount of data being created doubles every day, with 90% created in the last 2 years. Google processes 5000TB per hour. - Big data can be used to predict behavior, combine different data sources for insights, and create personalized services informed by a user's context. - When developing a big data strategy, companies should start by collecting their own data, appoint a dedicated team, look for connections in the data, develop a vision, and continuously learn and launch new services. - The

1. June 11, 2013 Iskander Smit, http://about.me/iskandr
Big Data & Social Media
Facebook Marketing Event 2013
http://vimeo.com/12187317

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Strategy director & managing labs.info.nl
member council Internet of Things
thinking online services since 1994

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Info.nl
§ internet agency since 1994
§ connecting the dots for brands that value the power of online
§ digital strategy, digital services, digital marketing, labs
§ networked agency with full-service core
§ partnership for social marketing with 77Agency
§ that is one of the 13 Facebook sPMD
§ social services: strategy, ux, apps, media, e-commerce management
§ clients amongst others: BVA Auctions, Greenwheels, bol.com, ABN Amro

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What is BIG in big data?

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(What is big today will be
common tomorrow)

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every day the amount of data
doubles
90% of all data originated in
the last 2 years
Google à 5000TB/h

7. June 11, 2013 https://www.facebook.com/facebook/photos_stream
110 songs have been played 40 billion times
150 billion friend connections

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http://villevivante.ch

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People
ThingsServices

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Volume
Velocity Variety
http://solveforinteresting.com/big-data-is-our-generations-civil-rights-issue-and-we-dont-know-it/

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Precogs
Memphis CRUSH, police combines
criminal data, personal data with
context data and real-time analytics

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Sources of data
§ Online behaviour. From search to browsing
§ Social. Facebook likes, youtube shares, linkedin connections, etc. etc.
§ E-mail. Google gmail
§ Internet of things. Just starting
§ Quantified self

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Source: behavior
Bonus kaart

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Source: our life
smart home

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Source: social behavior
Livehoods based on Foursquare

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Source: ourselves
From Fitbit to Moto X

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Ubiquitous time/location stamps
iBeacons

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Combining data
Facebook customer audiences

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Lookalike profiling expands the
profiles 10 times

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Endless source of data

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Technologies of Big Data
Hadoop, Mapreduce, Hive, …

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Components in a Big Data system

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3 layers (Cloudera)
§ substract
§ technologies: Open Commute, Linux, ZooKeeper, Puppetchef
§ services: Gimbal, Zigbee.
§ store
§ technologies: HDFS (Hadoop), Hive, Hbase
§ services: Amazon S3
§ compute
§ technologies: YARN, MapReduce, FlumeJava
§ software: Splunk, Palantir, Google Charts

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McKinsey Global Institute, May 2011.

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Predict behavior
ZestCash

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Brokers of data
Bazaarvoice

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Knowledge
medicine interactions

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Combining sources
Bina

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Big data analytics, still BI focused
MicroStrategy, Tableau

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A promise of Big Data analytics:
Do-It-Yourself
Business Intelligence

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Search the big data
Cloudera search

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Big data is de new online value
pagerank network+effect conversa0ons big+data

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Tiny services

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The value of big data is in the
personal services you create

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http://www.youtube.com/watch?v=pPqliPzHYyc

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With the predictive power of now,
you get just the thing you need to
know, right when you need it.

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From search to relevant agent
Google Now

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uncanny valley of relevancy

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private
generic
1000

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transparent
personal
1000

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anonymous
relevant now
1000
big data

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Products react to context
Nest

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Data driven serendipity
Peel

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The power of Big Data is
a new form of personal relevant
services

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Tension
predictiveness and serendipity
can become Big Data flow

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The value of big data is in the
personal services you create

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We live in The Matrix
PRISM / Google

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How to act
first steps in a big data strategy
https://vimeo.com/5550677

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Users
Rules
Data objects

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Data objects
§ Connected to each other by the use of all users
§ And also by their meta data
§ Value of relations emerges from frequence
§ Negative relations can appear

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Users
§ Relations per user with objects
§ Objects are no hub to relate users with each other
§ Objects are no hub to relate objects to users

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Rules
§ Repeating intelligence
§ Basis is ad-hoc connecting,
§ Can be rules for recognized repeating behavior
§ Connects objects to data

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Data intelligence
data science data intelligence
improvement 10% 10x
model goal predict/optimize create/change
decision algorithm human
data big/clean small/messy
communication equations stories
problem tactical strategic
Sean Gourley, Quid

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Creating an ad-hoc real-time
profile for the user of the
service.
Fueled by bol.com
recommendation API +
Facebook social graph

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The recipe.

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Steps in a datastrategy
1. Start with collecting data that is running through your systems
2. Appoint a special data team with several different roles
3. Look for the connections between the data streams
4. Develop a data vision
5. Make a plan, a strategy to execute
6. Learn & launch all the time

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Big data for intelligence =
story based data design

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Combine sources to
on-the-fly user profiles

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So to end some attention points
§ Go for the delta in data
§ Mix moment and insight
§ Be humble
§ Create serendipity
§ Learn and tune
§ Combine sources
§ Build internal support
§ Start!

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The value of big data is in the
(personal) services you create

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Thanks!
Iskander Smit
http://labs.info.nl
iskander@info.nl
+31624532388
@iskandr