Invited talk planned for STI summit in Russia in July 2013. Due to an error in visa I never made it to Russia. Here is the talk anyway. The first part is my standard big data talk. The second part is about the semantic web and big data.
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03
04
05
Index
The Big Data opportunity
What is Big Data?
Big Data risks
What role can
businesses play?
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Context: Telefonica
Digital
Conclusions
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And what about The
Semantic Web?
7. 7Telefonica Digital
But what is Big Data
Dave Feinleib, Forbes blog
03
1. Big Data is Only About Massive Data Volume
2. Big Data Means Hadoop
3. Big Data Means Unstructured Data
4. Big Data is for Social Media Feeds and Sentiment
Analysis
5. NoSQL means No SQL
Gartner’s Hype Cycle: technologies, use cases,
new sources of data
8. 8Telefonica Digital
A closer look at where Big Data sits
From a telco perspective
Type of Big
Data
OTT/Telco Cost of data
collection
By product/
seeking
Batch/real-
time
Strength of
telco?
Social media OTT Low Active Both No
Web logs Both Low Passive Both No
Network data
(telco)
Telco High Passive Both Yes
M2M (sensor)
data
Both High Active Both Might
Open data OTT Low Both Batch No
Transact. data Both Medium Passive Both No
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9. 9Telefonica Digital
But be aware of the privacy time bomb
Three Mile Island accident
killed the nuclear industry in
the US
Regulators are watching
Data “scandals” abound
“It’s Tracking Your Every Move and You May Not Even Know”
“Betrayed by our own data”
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14. 14Telefonica Digital
Society is also evolving, but in what direction?
Ignorance
• Customers are largely unaware of
what is happening
Trading
• Customers make an explicit trade-off
for each service
Wanting?
• Are customers wanting organizations
to use their (personal) data to improve
their lives?
Key evolving data concepts:
• Individual, aggregated, anonymized
• Customer consent (ex/implicit – opt-in/out)
• Legal ≠ accepted by society
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15. 15Telefonica Digital
PI Economy“Big Data”“Old wine in new bottles”
So how can businesses play in the Big Data space?
Different “business” models with different maturities and different risks
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Leverage data to
understand and
improve business
(x/up sell, churn)
and products
Data = improved
business
Recognize that
digital data is
delicate (privacy)
Turn that into an
opportunity
Data = risk =
business
Insights that help
improve
businesses and
governments
Data = business
Leverage data for
targeting users
with relevant ads
and higher CTR
and conversion
Data = better
advertising
M2M
Smart cities
Improve
services
Advertising Access to
insights
Become a
gatekeeper of
personal data
16. 16Telefonica Digital
Conclusions
Find your position on three key dimensions
“Bigness” of data
Value
“Bigness” of data “Bigness” of data
Privacyrisk
Nativebigdatatechnology
Apps
Insights
Processed
data
Raw data
Anonymous data
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