1. A Brief Introduction to Social Data
by Dion Hinchcliffe (@dhinchcliffe)
dion.hinchcliffe@dachisgroup.com
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Social As The Dominant Global Trend
The Adoption Rates of E-mail, Social Networks, and E2.0
1B 100%
projected
750M 75%
Enterprises
Global Users
Percent of
imate
high est
50%
500M e
low estimat
25%
250M
2006 2007 2008 2009 2010 2011
Consumer
Social E-mail Enterprise 2.0
Networks
Sources: comScore, Hitwise, and The Radicati Group, Forrester, APC, Intellicom, Neilsen
Norman Group, Social Business Council, NetStrategy/JMC
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Social Analytics
“The creation of typed signals by
listening to social ecosystems,
resulting in the ability to tap into
collective intelligence as well as
aggregate, mine, and predict
outcomes.”
getting value from what’s observable
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Hundreds of public social networks...
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...channel fragmentation 5
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Dozens of internal social channels
• E-mail
• Text messaging
• Instant messaging
• Meetings and conference calls
• Enterprise 2.0
• Social CMS
• Knowledge management
• Intranets
• Online communities
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Data (and knowledge) is increasingly visible in social channels
It no longer “evaporates” or is hidden
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And we now realize it’s part of a single continuum...
Social
Busine
enterp
rise ec s
osyste
s
m
rnet
t
ane
Inte
customers + extr
world
t
ane
business partners
intr
Web 2.0 integr
ated
vision
Crowdsourcing workers
Social Media Social CRM
Online Communities Enterprise 2.0
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But is all this observable information valuable?
story
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Observable work: The issues
• 1 day of week is spent by
workers looking for info to do
their jobs. Source: Forrester
• Half of work in developed
nations is tacit knowledge.
Source: McKinsey
• Social channels cause data
volumes to grow vastly after
several years. Source: Jive
• 80-90% of most business data is
submerged in IT systems and
not accessible. Source: Various
including Gartner, IDC, others
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“Information overload is not the problem. It’s
filter failure.” - Clay Shirky
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Our information landscape is now measured in
millions of exabytes
1 EB = 1,000,000,000,000,000,000 B = 1018 bytes = 1 billion gigabytes = 1 million terabytes
• Social ecosystems are largely responsible.
• The good news: Information is no longer
submerged.
• However, it is increasingly becoming an onslaught.
Visible
Knowledge Us
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Comparing data analytics with search
Seeing the Finding the
shape of the needle
haystack
analytics versus search
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value
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How do we get to the third wave?
• Cloud computing? SOA?
• Open APIs and supply chains?
• Decentralized IT?
• Better data warehouses?
• Improved search engines?
• Recommendation systems?
• Business re-engineering?
The Goal: Breaking down
• How about analytics? information silos and
obscured information inside
and outside of our
organizations to get to value
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Putting listening in context with data & analytics
Social Media
Universe
• Create scaled & integrated picture
• Identify participants & communities Listening
• Capture unmet needs Landscape
• Identify opportunities & crises
Global
Reach • Aggregate social media data
• Mine sentiment & trends Analytics &
• Derive strategic insight
• Develop effective responses Intelligence
• Provide dashboards and BI
1 Billion People Economy • Access all social touch points
+ of Scale • Engage with ecosystem Engagement
• Drive objectives and create value
• Ensure consistency of response Processes
You & Your Organization • Build new social capital
+ • Create conduit to social world
• Build skills and ability to execute Capability
3rd Parties (Partners, etc) Unified
• Develop ability to govern
Approach
• Assemble a Social Business
Acquisition
Capability
It’s the new flow of business
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The new flow of business
• Maintain an understanding of
everything the marketplace knows
• Be able to connect the dots of social
• Tap widely and deeply into the activity across all channels
top social channels • Wield strategic insight that can be
• Pick up important social leveraged across the organization
signals in near real-time Listen Analyze • Initiate responses systematically
• Centralized capacity to update from policy with less duplication and
listening capabilities as the with high degrees of automation
social marketplace continues • Share and provide access to data
to rapidly evolve and insight to all stakeholders
• Enable all stakeholders to
access vital social activity
informs
New products,
Social Business services, and
Capability products
informs Social
Business
Connect with customers in their Engage Processes
channel of preference to drive high
value activities such as better
customer care, product input,
innovation, and sales
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How will we listen?
http://apps.facebook.com/friendwheel
• Personally
- In our social environments
- On our devices
- With our social capital
- For us
• Using strategic tools
- To automate
- To scale
- With aggregate social capital
- For our businesses
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Strategic social media data analytics exists
• But are are just emerging from
infancy
• Focus primarily on the outside
world
• Strongly favor new social
environments over older style and
vertical communities
• Have limited analytics abilities
• Don’t connect well to existing
reporting tools and data
warehouses
• Are relatively expensive (compared
to free)
They also exist where you don’t
expect them
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Nascent social analysis: Reputation systems
• Plug-ins or E2.0 application features that
allow user feedback of contributions
• Including posts, comments, and even tags
• Example: LiquidPub
• Allow quality and portable reputations to be
established over time in E2.0 ecosystems
• Most useful for newish or large social
business environments
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What will social data analytics be used for?
• Sentiment analysis
• Expertise location
• Critical situation tracking
• Root cause analysis
• Trend extraction
• Sociology
• Knowledge mining & discovery
• Social capital management
• Social supply chain
• And much more
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What breakthrough will get us there?
Big Data: The Moving Parts
Increasing
Age & Maturity Hadoop Hive unsupervised learning
Vertica SciPy social media analytics
MapReduce sentiment analysis
Mahout
Esper predictive modeling
MATLAB Business
kdb BPO BI Objectives
Revolution R
Greenplum network analysis
ETL Netezza SPSS AMPL visualization
ECL Teradata SAS simulation
Fast Data Big Analytics Deep Insight
From http://blogs.zdnet.com/Hinchcliffe
the growth of data will be exponential for the foreseeable future
terabytes petabytes exabytes zettabytes
the amount of data stored by the average company today
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Social + data analytics = business intelligence
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Business Example
http://socialbusinessindex.com
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