A Brief Introduction to Social Data

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27 Σεπ 2011 (πριν από 5 χρόνια και 10 μήνες)

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A Brief Introduction to Social Data by Dion Hinchcliffe (@dhinchcliffe)

A Brief Introduction to Social Data
by Dion Hinchcliffe (@dhinchcliffe)
dion.hinchcliffe@dachisgroup.com
(cc) 2011 Dachis Group. Creative Commons. Some Rights Reserved.
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Social As The Dominant Global Trend
The Adoption Rates of E-mail, Social Networks, and E2.0
2011
2006
1B
750M
500M
250M
2007
2008
2009
2010
Sources:
Global Users
projected
Consumer
Social
Networks
E-mail
100%
75%
50%
25%
Enterprise 2.0
comScore, Hitwise, and The Radicati Group, Forrester, APC, Intellicom, Neilsen
Norman Group, Social Business Council, NetStrategy/JMC
high estimate
low estimate
Percent of
Enterprises
® 2011 Dachis Group.
What is social data?
3
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Social Analytics
4
getting value from what’s observable
“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.”
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Hundreds of public social networks...
5
...channel fragmentation
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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
6
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Data
(and knowledge)
is increasingly visible in social channels
7
It no longer “evaporates” or is hidden
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And we now realize it’s part of a single continuum...
8
Social Business
enterprise ecosystem
customers 
world
business partners
workers
Web 2.0
Crowdsourcing
Social CRM
Enterprise 2.0
Social Media
Online Communities
integrated vision
intranet
extranet
Internet
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But is all this observable information valuable?
9
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
10
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“Information overload is not the problem. It’s
filter failure.” - Clay Shirky
11
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Our information landscape is now measured in
millions of exabytes

Social ecosystems are largely responsible.

The good news: Information is no longer
submerged.

However, it is increasingly becoming an onslaught.
12
1 EB = 1,000,000,000,000,000,000 B = 10
18
bytes = 1 billion gigabytes = 1 million terabytes
Visible
Knowledge
Us
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Comparing data analytics with search
13
Seeing the
shape of the
haystack
Finding the
needle
versus
analytics
search
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14
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?

How about analytics?
15
The Goal:
Breaking down
information silos and
obscured information inside
and outside of our
organizations to get to value
® 2011 Dachis Group.
First, it’s about listening
16
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Putting listening in context with data & analytics
17
Social Media
Universe
1 Billion People
+
You & Your Organization
+
3rd Parties (Partners, etc)
Global
Reach
Economy
of Scale
Unified
Approach
Listening
Landscape
Analytics &
Intelligence
Engagement
Processes
Capability
Acquisition

Create scaled & integrated picture

Identify participants & communities

Capture unmet needs

Identify opportunities & crises

Aggregate social media data

Mine sentiment & trends

Derive strategic insight

Develop effective responses

Provide dashboards and BI

Access all social touch points

Engage with ecosystem

Drive objectives and create value

Ensure consistency of response

Build new social capital

Create conduit to social world

Build skills and ability to execute

Develop ability to govern

Assemble a
Social Business
Capability
It’s the new flow of business
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18
Listen
Analyze
Engage
Social Business
Capability
informs
informs

Tap widely and deeply into the
top social channels

Pick up important social
signals in near real-time

Centralized capacity to update
listening capabilities as the
social marketplace continues
to rapidly evolve

Enable all stakeholders to
access vital social activity

Maintain an understanding of
everything the marketplace knows

Be able to connect the dots of social
activity across all channels

Wield strategic insight that can be
leveraged across the organization

Initiate responses systematically
from policy with less duplication and
with high degrees of automation

Share and provide access to data
and insight to all stakeholders
Connect with customers in their
channel of preference to drive high
value activities such as better
customer care, product input,
innovation, and sales
New products,
services, and
products
Social
Business
Processes
The new flow of business
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How will we listen?

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
19
http://apps.facebook.com/friendwheel

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Strategic social media data analytics exists
20

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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21

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
Nascent social analysis: Reputation systems
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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?
Fast Data
Big Analytics
Deep Insight
Increasing
Age & Maturity
Big Data:
The Moving Parts
terabytes
petabytes
exabytes
zettabytes
the amount of data stored by the average company today
the growth of data will be exponential for the foreseeable future
MapReduce
Hadoop
kdb
Vertica
Netezza
Esper
Greenplum
ECL
Teradata
Hive
MATLAB
SciPy
SAS
Mahout
Revolution R
SPSS
AMPL
network analysis
predictive modeling
simulation
visualization
unsupervised learning
social media analytics
sentiment analysis
BPO
BI
Business
Objectives
From
http://blogs.zdnet.com/Hinchcliffe
ETL
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Social + data analytics = business intelligence
(cc) 2011 Dachis Group. Creative Commons. Some Rights Reserved.
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http://socialbusinessindex.com
Business Example
Thank you