Can we see additional value in linking and exploiting big data for business and societal benefit? If we bring together numerous data sources to provide a single reference point then we start to derive new value. Until then, we simply risk creating new data silos.

1. What is Big Data?
Rajendra Akerkar
rak@vestforsk.no
Presented at Université Jean Monnet – Université de Lyon France, June 10, 2013

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Hype around Big Data
Today, the difference between success and failure is the ability to monetize a
new class of data. It’s ironic that, despite billions of dollars spent on business
intelligence systems, we are still data‐bankrupt.
– Roman Stanek, Founder and CEO of Good Data

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Source: Bloor Group

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The rise and rise of Big Data

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Share of the digital universe by India and China

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What is Big Data?
videos & photos
email
mobile GPS
social
Big
Data
Data that is too big, moves too fast, or doesn’t fit the structures of your
database architecture

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Fallacy!
 Data does provide information
 Big Data  Big Insight
 Information must be:
 Interpretable
 Relevant
 Novel
 The insight we can derive is a tiny fraction of data, we need
to collect even more data and use more powerful analytics
to increase the likelihood of finding it.

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 The amount of information one can extract
from the data is always much less than the
data volume

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A step forward in business intelligence and
analytics
Can we see additional value in linking and exploiting big data
for business and societal benefit?
 If we bring together
numerous data sources
to provide a single
reference point then
 we start to derive new
value.
 Until then, we simply
risk creating new data
silos.

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Detecting Financial &
Insurance Fraud
Integrating Information from a
variety of sources yields significant
intelligence
Moving from a single document
view to a network view significantly
improves risk scoring effectiveness
 Benefits
 Major International Banks detect
fraud > $50M
 Reduce costs to end‐users
 Increased trust

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Providing a competitive
advantage in manufacturing
Volvo – rapidly deriving intelligence from
vehicle sensor data
 Reduction in cycle time for fault
rectification
 Predictive maintenance
 Location specific design enhancements
Proctor and Gamble ‐ using data to
“digitise” operations
 Remove inefficiencies from production
 Reduce inventory across supply chain
 Analytics and visualisation to aid
decision making

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Google predicted the spread of flu in
real time
 after analyzing two datasets,
 50 million most common terms that Americans type,
 data on the spread of seasonal flu from public health
agency
 tested a mammoth of 450 million different mathematical
models to test the search terms, comparing their
predictions against the actual flu cases
 model was tested when H1N1 crisis struck in 2009 and
gave more meaningful and valuable real time
information than any public health official system.
(Reference: http://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544002695)

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There has always been Big Data…
Its just that now we can actually capture and mine
it effectively.
Canadian Tar Fields

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Knowledge is knowing when and how to use certain
info and insights.
If someone digests the info+insight, it become his knowledge

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Not all Big Data is created Equal
Planet Google and friends are the outliers
The Norm
Large Telco
.
Google, Facebook, Twitter –are outliers
that are in a class of their own. And their
requirements are significantly different
to large enterprise businesses, let alone
the normal enterprise business and SME.

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Definition(s) of “big data”
Big Data is a term encompassing the use of
techniques to capture, process, analyse and
visualize potentially large datasets in a
reasonable timeframe not accessible to
standard IT technologies.
By extension, the platform, tools and
software used for this purpose are collectively
called ‘Big Data technologies’
(Networked European Software and Service Initiative, 2012).

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Or, in other words,
•
•
•
•
•
Big Data is data
in volumes too large to
process by
traditional methods.
Unable to handle large data volumes & diversity of data
Iterative, brute‐force and slow process
Lack of ad‐hoc data navigation across events and time
Focused on structured data that is warehoused
Web analytics solutions force real‐time events into rigid
schemas in DBs

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What is a Big Data problem?

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3 Vs
 For Volume
 How to convert massive amounts of data into information,
meaning, and insight useful for human decision‐making.
 For dealing with Variety
 Use experience in using ontologies, domain models, or
vocabularies, to support semantic interoperability and
integration
 For Velocity
 How to use dynamically created models of new objects,
concepts, and relationships and uses them to better
understand new clues in the data that capture rapidly
evolving events and situations.

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What happens if the raw data you are
injecting into your system is
incomplete or formatted incorrectly
from the get‐go?
Additional attributes
Venue
Vocabulary
Veracity

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 People will be interested in value
‐ extracting value from Big Data

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Is it actionable ?
 The first three Vs are just measures of data
— how much, how fast, and how diverse?
 NOT an actionable, complete definition
 Definition of big data must concede that:
 Exponential data growth makes it continuously difficult to
manage — store, process, and access.
 Data contains non‐obvious information that companies can
discover to enhance business outcomes.
 Measures of data are relative; one company’s big data is
another company’s peanut.

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So, the pragmatic definition
store
process
access
Big Data is the frontier of a
company’s ability to store,
process, and access all the
data it needs to operate
effectively, make decisions,
reduce risks, and serve
customers.

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Big Data for Everyone
• Big data is not just for data scientists and special
projects
• Its for decision makers and data consumers
• It needs to be anchored in the real world
Analyst
Consumers

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Who is benefitting from Big Data?

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Correlation versus causation versus “what’s good
enough for the job”
Source: Columbia University
Oncologists might benefit from seeing the similarities among cells in a
biopsy, but targeting certain markers doesn’t guarantee you can cure
someone’s cancer.

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Big Data analytics – the need for new approach

Scalablility
No
Yes
Ingest high
Volumes of data
(all available data) no
Yes
Sampling of data Yes
NO
Variety of data
(structured, semistructured,
unstructured)
No
Simultaneous data
and query
processing
No
Faster access to
all relevant
information
No
Analyze data at
high rates(GB/sec No
Accuracy in
anlytical models
Competitive Advantage
Challenges
Traditional New
approach approach
The questions that are answered
What’s the best that can happen?
Optimization
What will happen next?
What if these trends continue?
Why is this happening?
Alerts
Predictive
Analysis
Forecasting
Statistical
Analysis
What actions are needed?
Yes
Query
Drilldown
Adhoc
reports
Yes
Std
reports
Yes
Do You have opportunity or a problem?
How many, how often,, where?
What happened?
Degree of Intelligence
Yes
Taking unstructured data into account
No
Yes

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BIG DATA Research Focus

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VALUE from harnessing the challenges
 Present‐day focus devoted to business intelligence and targeted
analytics needs, not to serve complex personal and collective
human requirements
 e.g., empower human in health, fitness and well‐being; better
emergency management that is highly personalized.
 Integrate real‐world complexity: multi‐modal and multi‐sensory
nature of real‐world and human perception
 Need deeper understanding of data and its role to information
 e.g., skew, coverage
 Human involvement and guidance
 Heading to actionable information, understanding and insight right in
the context of human activities
 Bottom‐up & Top‐down processing
 Infusion of models and background knowledge (data + knowledge +
reasoning)

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Data should provide VALUE from
harnessing the challenges posed by
volume, velocity, variety and veracity
of big data, to provide actionable
information and improve decision making

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Read this book!
Publisher: Taylor & Francis Group/CRC Press
http://www.taylorandfrancis.com/books/details/9781466578371/

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Thank you !