Transcript Slide 1

Big Data
Mark Theissen
CEO, Cirro, Inc.
[email protected]
We have been wrestling with data a long time
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Big Data… everyone is talking about it
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but what does it mean?
“Big data is a term applied to data sets
that are large, complex and dynamic (or a
combination thereof) and for which there
is a requirement to capture, manage and
process the data set in its entirety, such
that it is not possible to process the data
using traditional software tools and
analytic techniques within tolerable time
frames.”
How Big is Big Data?
In 2011, the amount of information created and replicated will surpass 1.8
zettabytes (1.8 trillion gigabytes) - IDC
Data volumes growing at a 60% CAGR - IDC
4.4 million jobs created by 2015 to support big data – Peter Sondergard,
Gartner
The average $250m 500 person company generates over 170TB of data
annually – Information Week
Are there different types?
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Structured
Semi-Structured
Unstructured
That Hadoop Thing
• Most popular technology for processing big data
• Open-source software framework for storing,
processing and analyzing big data
• Made up of many sub-components or projects
• Commercially available
• Why important?
• Massive parallel processing
• Very low cost
What are the challenges?
• The world of data going forward is
distributed
• Performance at scale is the challenge of
big data
• Leveraging existing investments
• Another data silo
• Requires new skills
So how are people approaching this?
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So how are people approaching this?
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So how are people approaching this?
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Case study – Fortune 100 Media &
Entertainment company
Challenge
• Analyze interactive experiences
across console, online, mobile
and social network platforms
• Inability to join data across
different platforms
• Analyst desire ad-hoc data
exploration
Solution
• Cirro Analyst, Cirro Data Hub
• Tableau
• Cloudera
Benefits
• Ability to quickly analyze
clickstream data with advertising
data
• Reduce IT support requirements
• Deliver improved target marketing
campaigns
it Case study – Major Music Publisher
Challenge
• Analyze nightly music downloads
from major retail distribution
outlets
• Analyst cannot explore data
sources in a timely fashion
• Eliminate overhead,
administration and costs of
virtualization technology
• No ability to join structured and
unstructured data sources
• Improve long-term artist success
Solution
• Cirro Analyst, Cirro Data Hub
• Hortonworks
Benefits
• Improve predictive analytics of
music sales
• Enable data mash-ups across
heterogeneous data sources
• Streamlined analysis of nightly
music sales activity
• Deliver superior marketing results
to recording artists
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In Summary
Bringing Big Data to the
Desktop
Copyright 2012 Cirro Inc. - all rights reserved