THE FUTURE HAS NEVER BEEN SO OPENNOVEMBER 6 / THE NEWSEUM / WASHINGTON D.C.

Track 2:Red Hat Cloud IaaS

Customer Success Stories11:00 A.M. – 11:45 A.M.

Speakers Include:

•Wolf Tombe, CTO, U.S. Customs & Border Protection, DHS

•Hoot Thompson, System Engineer, NASA Goddard

•Dr. Christopher Jacobson, Chief Technologist, U.S. Federal, Systems & Technology Group, IBM

•Moderator: Bob Kozdemba, Principal Solutions Architect, Public Sector, Red Hat

THE FUTURE HAS NEVER BEEN SO OPENNOVEMBER 6 / THE NEWSEUM / WASHINGTON D.C.

Track 2:Big Data as a Service

11:50 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 external partners to help meet our mission and goals.

Triumph through crowd-sourcing. Innovation though collaboration.

© Hortonworks Inc. 2013

A Traditional Approach Under Pressure

Page 10

REPOSITORIES

Existing Sources (CRM, ERP, Clickstream, Logs)

RDBMS EDW MPP

Emerging Sources (Sensor, Sentiment, Geo, Unstructured)

Business Analytics Custom Applications Packaged

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

Page 12

REPOSITORIES

Existing Sources (CRM, ERP, Clickstream, Logs)

RDBMS EDW MPP

Emerging Sources (Sensor, Sentiment, Geo, Unstructured)

MANAGE & MONITOR

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