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Track 2:
Big Data as a Service11:50 A.M. – 12:35 P.M.
SPEAKERS INCLUDE:
• Chris Layton, HPC Systems Administrator, National Center for Computational Sciences, Oak Ridge National Laboratory
• Xavier Hughes, Chief Innovation Officer, Dept. of Labor
• Dr. Dave Bauer, Chief Scientist, Data Tactics
• John Kreisa, VP of Strategic Marketing, Horton Work
• Moderator: Toan Do, Director, Intelligence Programs, Red Hat
Daniel Ricciuto (left) and Peter Thornton (right) using the Exploratory Data analysis ENvironment (EDEN) to visually explore multiple Community Land Model (CLM) simulation data sets. In
particular, Ricciuto and Thornton are analyzing sensitivities in the Amazonia region using the interactive visual analytics in EDEN on EVEREST's Planar display.
Chad Steed using EDEN on EVEREST to explore 1000CLM4 simulations (81 parameters and 7 output variables) on the previous
version of the EVEREST display wall.
Big & open data provides an opportunity for externalpartners to help meet our mission and goals.
Triumph through crowd-sourcing. Innovation though collaboration.
© Hortonworks Inc. 2013
A Traditional Approach Under Pressure
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REPOSITORIES
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Existing Sources (CRM, ERP, Clickstream, Logs)
RDBMS EDW MPP
Emerging Sources (Sensor, Sentiment, Geo, Unstructured)
Business Analytics
Custom ApplicationsPackaged
Applications
Source: IDC
2.8 ZB in 2012
85% from New Data Types
15x Machine Data by 2020
40 ZB by 2020
© Hortonworks Inc. 2013
Most Common NEW TYPES OF DATA
1. SentimentUnderstand how your customers feel about your brand and products – right
now
2. ClickstreamCapture and analyze website visitors’ data trails and optimize your website
3. Sensor/MachineDiscover patterns in data streaming automatically from remote sensors and
machines
4. GeographicAnalyze location-based data to manage operations where they occur
5. Server LogsResearch logs to diagnose process failures and prevent security breaches
6. Unstructured (txt, video, pictures, etc..)Understand patterns in files across millions of web pages, emails, and
documents
Value
+ Keep existing data
longer!
© Hortonworks Inc. 2013
An Emerging Data Architecture
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Existing Sources (CRM, ERP, Clickstream, Logs)
RDBMS EDW MPP
Emerging Sources (Sensor, Sentiment, Geo, Unstructured)
OPERATIONALTOOLS
MANAGE & MONITOR
DEV & DATATOOLS
BUILD & TEST
Business Analytics
New Custom Applications
PackagedApplications
© Hortonworks Inc. 2013
Federal Government & Big Data
• Law Enforcement/Security
–Store and process biometric identification for individuals
–Multi-modal ID increases accuracy, but requires more data storage and parallel processing
for distinct matching algorithms:
–Facial Recognition, Fingerprints, Voice, Gait
•Environmental Protection Agency (EPA)
–Capture machine generated data to monitor air, water & land quality
–Combine sensor data and social media / sentiment analysis
•Social Security Administration (SSA)
–Finding fraudulent claims for benefits using big data analysis to look for patterns of fraudulent
behavior
