Semantics Approach to Big Data and Event Processing: an introduction focused on velocity and variety Prof Emanuele Della Valle - DEIB Politecnico di Milano

1. BigData
Semantic Approach to
Big Data and Event Processing
Big Data:
an introduc/on focused on
Velocity and Variety
Emanuele Della Valle
DEIB - Politecnico di Milano
@manudellavalle
emanuele.dellavalle@polimi.it
hAp://emanueledellavalle.org

2. BigData
Who I am
• Assistant Professor at
Politecnico di Milano
• Expert in seman/c and stream
compu/ng technologies
• Inventor of stream reasoning:
an approach to master the
velocity and the variety
dimen/ons of Big Data at once
• 15 years of experience in
research and innova/on
projects
• startupper: fluxedo.com
6/10/2015
@manudellavalle - hAp://
emanueledellavalle.org
@manudellavalle
hAp://emanueledellavalle.org
hAp://streamreasoning.org
hAp://fluxedo.com
2

3. BigData
Agenda
• Why now?
• Its value
• What is it?
• Paradigm shiOs enabled
• Tools
• Market Landscape
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 3

4. BigData
Why now? 1/5
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 4

5. BigData
Why now? 2/5
[source: McKinsey, 2011]
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Hard-drive are
becoming cheaper
We are all data
producers
We do it on a
regular basis
Data are
growing faster
than IT spending
Data gets
cumulated …
… everywhere

6. BigData
Why now? 3/5
[source: hAp://www.intel.com/newsroom/bigdata/]
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We do it on a
regular basis

7. BigData
Why now? 4/5
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[source: hAp://www.go-gulf.com/blog/60-seconds/]

8. BigData
Why now? 5/5
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[source: hAp://www.go-gulf.com/blog/60-seconds-v2/]

9. BigData
Its value 1/3
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 9

10. BigData
Its value 2/3
[source: McKinsey, 2011]
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healthcare
Public
Administra/ons
Personal loca/on

11. BigData
Its value 3/3
[source: McKinsey, 2011]
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margin
jobs
skills

12. BigData
Data vs. Analy/cal vs. Execu/on
Capability
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Intensity
90's 2000's 2010's 2020's
Data Availability
Execution Capability
Analytical Capability
Widening Gap

13. BigData
… so what's Big Data?
[source: IBM, 2012]
Analysis of the answers of
1144 responders from
organiza/ons that run Big
Data projects
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14. BigData
Characteris/cs 1/5
[source: IBM, 2012]
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15. BigData
Characteris/cs 2/5
[source: IBM, 2012]
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16. BigData
Characteris/cs 3/5
[source: IBM, 2012]
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17. BigData
Characteris/cs 4/5
[source: IBM, 2012]
the one certainty about uncertainty
is that it is not likely to go away
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18. BigData
Characteris/cs 5/5
[source: IBM, 2012]
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19. BigData
Paradigm ShiOs Enabled 1/4
[source: Marc Andrews, 2014]
Leverage more of the data being captured
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20. BigData
Paradigm ShiOs Enabled 1/4
[source: Marc Andrews, 2014]
Leverage more of the data being captured
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 20

21. BigData
Paradigm ShiOs Enabled 2/4
Data-driven explora/on looking for correla/on
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[source: Marc Andrews, 2014]

22. BigData
Paradigm ShiOs Enabled 2/4
Data-driven explora/on looking for correla/on
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 22
[source: Marc Andrews, 2014]

23. BigData
Paradigm ShiOs Enabled 3/4
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Reduce effort required to leverage data
[source: Marc Andrews, 2014]

24. BigData
Paradigm ShiOs Enabled 3/4
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 24
Reduce effort required to leverage data
[source: Marc Andrews, 2014]

25. BigData
Paradigm ShiOs Enabled 4/4
Leverage data as it is captured
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 25
[source: Marc Andrews, 2014]

26. BigData
Paradigm ShiOs Enabled 4/4
Leverage data as it is captured
6/10/2015 @manudellavalle - hAp://emanueledellavalle.org 26
[source: Marc Andrews, 2014]

27. BigData
Combining the Vs?
• Volume + Velocity + Variety = hard deal
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Volume
months days hours min. sec. ms.
Velocity
ZB
EB
PB
TB
GB
MB
KB
Variety

28. BigData
Combining the Vs?
• Volume + Velocity + Variety => high value
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Value
ms. sec. min. hours days months years
velocity
Variety

29. BigData
Credits
• Big Data: the next fron/er for innova/on, compe//on, and
produc/vity. McKinsey Global Ins/tute. May, 2011.
– hAp://www.mckinsey.com/insights/business_technology/big_data_the_next_fron/er_for_innova/on
• Analy/cs: The real-world use of big data. IBM Ins/tute for Business
Value In collabora/on with Saïd Business School at the University of
Oxford. 2012
– hAp://www-03.ibm.com/systems/hu/resources/the_real_word_use_of_big_data.pd
• Big Data & Analy/cs: Next Genera/on Architecture and Capabili/es.
Marc Andrews, 2014
– hAps://www.ibm.com/partnerworld/wps/servlet/RedirectServlet?cmsId=isv_ast_smp_ecosystem-
webcasts&aAachmentName=Data_Warehouse_deck.pdf
• Hype Cycle for Big Data, 2012. Gartner, 2012
– hAps://www.gartner.com/doc/2100215/hype-cycle-big-data-
• Big Data Landscape, version 3.0. MaA Turck, and Su/an Dong, 2014
– hAp://pt.slideshare.net/mjO01/big-data-landscape-maA-turck-may-2014
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30. BigData
Semantic Approach to
Big Data and Event Processing
Thank you!
Any Ques/on?
Emanuele Della Valle
DEIB - Politecnico di Milano
@manudellavalle
emanuele.dellavalle@polimi.it
hAp://emanueledellavalle.org