1. Big Data Mark Theissen CEO, Cirro, Inc. mtheissen@cirro.com

2. We have been wrestling with data a long time it

3. Big Data… everyone is talking about it but what does it mean? it “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.”

4. 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

5. Are there different types? it Structured Semi-Structured Unstructured

6. 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

7. 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

8. So how are people approaching this? it

9. So how are people approaching this? it

10. So how are people approaching this? it

11. Case study – Fortune 100 Media & Entertainment company it 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

12. Case study – Major Music Publisher it 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

13. In Summary it

14. Bringing Big Data to the Desktop Copyright 2012 Cirro Inc. - all rights reserved