Big data is all about comprehending the data sets. It is a term applied to data sets whose size or complexity is beyond the ability of commonly used software tools to capture, manage, and process the data within a reasonable elapsed time. Thus a big data set is just too big to be handled and analyzed by traditional methods and protocols of an organization; a data set of 250 megabyte can already push the limits of the data capabilities because people are unable to retrieve and analyze the data using tools like spreadsheet applications or even a tablet computer. In any case, there is a limit to how much data leads to more knowledge.
With leading CIOs we will discuss the the different perspectives on dealing with the big data revolution that goes beyond the obvious constituency of high-energy particle physics and astronomy. Where small and medium science is suffering from big data problems since most of the attention is focused on the on top 1% producers / consumers of scientific data: the long tail of Big Data. How can campuses share their experience and start collaborations on dealing with the sheer amount of data.
Breaking the Kubernetes Kill Chain: Host Path Mount
Big Data Big Deal!
1. BIG DATA
A L L E Y
Big Data Big Deal!
Harold Teunissen et al.
#TNC2013, June 2013
A Layman’s Perspective
2. Big Data Big Deal! - #tnc2013 - Maastricht, NL
Big Twin
2
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Big Network
3
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Big Map
4
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Big Hobbit
5
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Big Organization
6
• All ICT activities for Higher Education and Research in the
Netherlands are under the SURF umbrella
Shared Professional and
Educational Services
Scientific Computing &
Data
Commercial ICT
Products & Services
National Research &
Education Network
eScience Collaboration
and Tools
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Big Hype
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Big Jeopardy
8
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Big Clue
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42
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Big Question
10
WHAT IS THE MEANING
OF LIFE, THE UNIVERSE
AND EVERYTHING?
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Big Thought
11
Source & Copyright 1981: BBC
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Big Panic
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Big Invasion
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Big Volume
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Big Data?
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Big Data
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Big Entropy
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KNOWLEDGE
CHAOS
Too Big
Data
Available Processing Power
AmountofData
Max. Available
Processing Power
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Big One
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P
1.3 million video views
30 hours of video uploaded
2+ million queries
61,000+ hours of music
100+ new accounts
277,000 logins
6 million facebook views
320+ new accounts
100,000 new tweets
3,000 photo uploads
20 million photo views
Source: Intel
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Big Velocity
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Big Variety
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Big Query
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Big Chasm
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Source: Geoffrey A. Moore c.s.
Techies Visionaries Pragmatics Conservatives Laggards
Chasm
Customers either want...
...solutions
and convenience
...technology and
performance
time
#ofcustomers
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Big Green
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Big Security
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Big Tail a Big Fail?
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# of researchers
BigDataScale
LONG TAIL OF SCIENCE
Really
Really
Big Data
Little
Big Data