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Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
Small Data and Big Analytics: In the Supercomputing Dojo
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Small Data and Big Analytics: In the Supercomputing Dojo

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  • 1. Small Data and Big Analytics: In the Supercomputing Dojo Richard Beckwith, Adam Laskowitz, and ken anderson SC13 Denver, CO November 18, 2013 User Experience Research, Intel Labs Intel Confidential — Do Not Forward
  • 2. People need a simple way to collect and consume data 2
  • 3. Big data doesn’t matter for the Little Guy 3
  • 4. Big analytics matter for the Little Guy 4
  • 5. Full Bleed Image 5
  • 6. 6
  • 7. 7
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  • 10. Sometimes data can be oversimplified 10
  • 11. 11
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  • 14. Simplicity with Adequacy “It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.” − Albert Einstein, From “On the Method of Theoretical Physics,” 14
  • 15. Simplicity Takes Work Adequacy requires:  Lidar data for community  Wind speed and direction  As many sources as possible  Pollen models based on geo-located source information  All relevant sources  Air pollution measurements  All species of pollutants deemed interesting  Pollution source maps by pollutant  Including traffic data  Monte Carlo modeling for various proposed accountings for measured data 15
  • 16. Simplicity Could Use a Supercomputer 16
  • 17. Intel Confidential — Do Not Forward

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