Data is exponentially increasing in both types and volumes, creating opportunities for businesses. Watch this video and learn from three Big Data experts: John Kreisa, VP Strategic Marketing at Hortonworks, Imad Birouty, Director of Technical Product Marketing at Teradata and John Haddad, Senior Director of Product Marketing at Informatica. Multiple systems are needed to exploit the variety and volume of data sources, including a flexible data repository. Learn more about: - Apache Hadoop 2 and YARN - Data Lakes - Intelligent data management layers needed to manage metadata and usage patterns as well as track consumption across these data platforms.

1. Quick Housekeeping
Q&A box is available for your questions
Webinar will be recorded
Thank You for joining!
© Hortonworks Inc. 2014

2. Hadoop 2.0: YARN to Further
Optimize Data Processing
© Hortonworks Inc. 2014

3. Your Speakers
John Kreisa, VP Strategic Marketing, Hortonworks
Imad Birouty, Director, Technical Product
Marketing, Teradata
John Haddad, Senior Director, Product
Marketing, Informatica
© Hortonworks Inc. 2014

4. John Kreisa, VP Strategic Marketing, Hortonworks
@marked_man
© Hortonworks Inc. 2014

5. Big Data Market Trends and Predictions
Big
Data
Explosion
© Hortonworks Inc. 2014
% by which org’s
leveraging modern
info management
systems outperform
peers by 2015
85%
from new
data types
ñ
Hadoop
enabled
DBMS’s
50x
data growth
2010 to 2020
1 Zettabyte (ZB)
=
1 Billion TBs
15x
growth rate of
machine
generated data
by 2020
The US has 1/3 of the world’s data
Big Data is 1 of 5 US GDP Game Changers
$325 billion incremental annual GDP from big data analytics
in retail and manufacturing by 2020

6. Existing systems under pressure
Business
Analy4cs
RDBMS
EDW
NoSQL
© Hortonworks Inc. 2014
DATA
SYSTEM
APPLICATIONS
REPOSITORIES
SOURCES
Exis4ng
Sources
Custom
Applica4ons
(CRM,
ERP,
Clickstream,
Logs)
Packaged
Applica4ons
2.8
ZB
in
2012
85%
from
New
Data
Types
15x
Machine
Data
by
2020
40
ZB
by
2020
Source: IDC
OLTP,
ERP,
CRM
Systems
Unstructured
documents,
emails
Server
logs
Clickstream
Sen>ment,
Web
Data
Sensor.
Machine
Data
Geoloca>on

7. Hadoop with YARN Compliments Existing Architecture
© Hortonworks Inc. 2014
DEV
&
DATA
TOOLS
Build &
Test
OPERATIONS
TOOLS
Provision,
Manage &
Monitor
DATA
SYSTEM
REPOSITORIES
SOURCES
RDBMS
EDW
NoSQL
OLTP,
ERP,
CRM
Systems
Documents,
Emails
Web
Logs,
Click
Streams
Batch Interactive Real-Time
Social
Networks
(Hadoop Distributed File System)
Machine
Generated
HDFS
Sensor
Data
Geoloca>on
Data
APPLICATIONS
Business
Analy4cs
Custom
Applica4ons
Packaged
Applica4ons
YARN: Data Operating System
1 ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° N

8. Hadoop: Typically used for new analytic apps
SCALE SCOPE
© Hortonworks Inc. 2014
New Analytic Apps
New types of data
LOB-driven

9. Unlock Value in New Types of Data
1. Social
Understand how people are feeling and interacting – right now
2. Clickstream
Capture and analyze website visitors’ data trails and optimize your
website
3. Sensor/Machine
Discover patterns in data streaming from remote sensors and
machines
4. Geographic
Analyze location-based data to manage operations where they occur
5. Server Logs
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
© Hortonworks Inc. 2014
Value
+ Online archive
Data that was once purged or moved
to tape can be stored in Hadoop to
discover long term trends and
previously hidden value

10. New Analytic Applications on Hadoop
Industry Use Case Type of Data
Financial Services
© Hortonworks Inc. 2014
New Account Risk Screens Text, Server Logs
Trading Risk Server Logs
Insurance Underwriting Geographic, Sensor, Text
Telecom
Call Detail Records (CDRs) Machine, Geographic
Infrastructure Investment Machine, Server Logs
Real-time Bandwidth Allocation Server Logs, Text, Social
Retail
360° View of the Customer Clickstream, Text
Localized, Personalized Promotions Geographic
Website Optimization Clickstream
Manufacturing
Supply Chain and Logistics Sensor
Assembly Line Quality Assurance Sensor
Crowdsourced Quality Assurance Social
Healthcare
Use Genomic Data in Medical Trials Structured
Monitor Patient Vitals in Real-Time Sensor
Pharmaceuticals
Recruit and Retain Patients for Drug Trials Social, Clickstream
Improve Prescription Adherence Social, Unstructured, Geographic
Oil & Gas
Unify Exploration & Production Data Sensor, Geographic & Unstructured
Monitor Rig Safety in Real-Time Sensor, Unstructured
Government
ETL Offload in Response to Federal Budgetary Pressures Structured
Sentiment Analysis for Government Programs Social

11. Hadoop: YARN Driven MDA Leads to a Data Lake
SCALE SCOPE
© Hortonworks Inc. 2014
A Modern Data Architecture/Data Lake
RDBMS
MPP
EDW
New Analytic Apps
New types of data
LOB-driven
Batch Interactive Real-Time
YARN: Data Operating System
1 ° ° ° ° ° ° ° ° °
HDFS
(Hadoop Distributed File System)
° ° ° ° ° ° ° ° ° N
Data Lake
An architectural shift in the data
center that uses Hadoop to
deliver deeper insight across a
large, broad, diverse set of data
at efficient scale

12. Integrating with Existing Investments
© Hortonworks Inc. 2014
DATA
SYSTEM
APPLICATIONS
SOURCES
RDBMS
EDW
MPP
Batch Interactive Real-Time
HDFS
(Hadoop Distributed File System)
Emerging
Sources
(Sensor,
Sen4ment,
Geo,
Unstructured)
BusinessObjects BI
DEV
&
DATA
TOOLS
OPERATIONAL
TOOLS
Exis4ng
Sources
(CRM,
ERP,
Clickstream,
Logs)
INFRASTRUCTURE
YARN: Data Operating System
1 ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° N
SOURCES
OLTP,
ERP,
CRM
Systems
Documents,
Emails
Web
Logs,
Click
Streams
Social
Networks
Machine
Generated
Sensor
Data
Geoloca>on
Data
Viewpoint

13. Imad Birouty, Director, Technical
Product Marketing, Teradata

14. Analysts Recommend:
Shift from a Single Platform to an Ecosystem
“We will abandon the old models
based on the desire to implement
for high-value analytic
applications.”
"Logical" Data Warehouse

15. Marketing
Applications
Business
Intelligence
Data
Mining
Math
and Stats
Languages
ANALYTIC
TOOLS & APPS
Customers
Partners
Business
Analysts
Data
Scientists
USERS
UNIFIED DATA ARCHITECTURE
MOVE MANAGE ACCESS
DATA WAREHOUSE
DISCOVERY PLATFORM
ERP
SCM
CRM
Images
Audio
and Video
Machine
Logs
Text
Web and
Social
SOURCES
DATA
PLATFORM
Marketing
Executives
Operational
Systems
Frontline
Workers
Engineers
Fast Loading
Filtering and
Processing
Online Archival
Business Intelligence
Predictive Analytics
Operational Intelligence
Data Discovery
Path, graph, time-series analysis
Pattern Detection

16. Marketing
Applications
Business
Intelligence
Data
Mining
Math
and Stats
Languages
ANALYTIC
TOOLS & APPS
Customers
Partners
Business
Analysts
Data
Scientists
USERS
UNIFIED DATA ARCHITECTURE
MOVE MANAGE ACCESS
DATA WAREHOUSE
DISCOVERY PLATFORM
ERP
SCM
CRM
Images
Audio
and Video
Machine
Logs
Text
Web and
Social
SOURCES
DATA
PLATFORM
Marketing
Executives
Operational
Systems
Frontline
Workers
Engineers

17. Data Lake Overview
• The single source of raw, historical, and real-time
operational data
• The ability to cost effectively
explore data sets of unknown,
under-appreciated, or
unrecognized value
• The reduction of LOB specific
big data environments, which
reduces costs and analytical
discrepancies
• The co-location of data sets to
enable light, on-the-fly integration

18. Approaches to Data Integration
Schema on Write
• Well understood data
• Relational integrity
• Storage efficiency
Schema On Read
• Dynamic data
• Reduced coordination
• Human readable
Data Warehouse
Data Lake

19. The “Capture Everything” Approach
“Capture only
what’s needed”
IT delivers a platform for
storing, refining, and
analyzing all data
sources
Business explores data
for questions worth
answering
Big Data Method
Multi-structured & Iterative
Analysis
IT structures the data to
answer those questions
Business determines
what questions to ask
Classic Method
Structured & Repeatable
Analysis
“Capture in case
it’s needed”

20. Automobile Sensor Data
Use Case
Value from combining business data with detail data
• Determine which cars to recall for bad battery lot
> Business data held in data warehouse
> Detailed sensor data held in data lake
> Query combines data
> Determine which cars to repair
TERADATA
PRODUCTION
DATA
• VINs
• Service
records
• Warranty data
• DTC
descriptions
HADOOP
RAW MULTI-STRUCTURED
DATA
• Battery
Temperature
Sensor data
Battery Temperature vs. Air Temperature

21. Customer Value Based on Social Influence
Use Case
HADOOP
TERADATA
ASTER
DATABASE
TERADATA
DATABASE
• Determine high value
customers based on history
• Determine customer value
based on social influence
• Determine
customer
sentiment
<=
• Determine
customer
sphere of
influence
$$

22. Data Optimization for the
Modern Data Architecture
John Haddad, Senior Director, Product
Marketing, Informatica

23. The Big Data Journey
The Big Data Journey
Optimize infrastructure for
performance, cost, &
scalability
A single place to
manage the supply and
demand of data
Real-time proactive
customer engagement
Data Warehouse
Optimization
Real-Time
Customer Analytics
Managed Data
Lake
Big Data
business
initiatives
IT driven Business driven

24. Proactive Customer Engagement
Web Logs
Clickstream Data
Streaming
Big Data Integration / Analytics
Master
Data
Mgmt Financial Advisors
Integration
& Quality
Customer / Product
Master
Customer
Customer
Smartphone
Real-Time
Event
Processing
Visualization
Social Data / Signals
Social Data
Connector
FIX, SWIFT,
Market Data
Customer Portal
DATA
PLATFORM
DISCOVERY
PLATFORM
DATA
WAREHOUSE

25. Proactive Patient Member Engagement
Web Logs
Clickstream Data
Streaming
Big Data Integration / Analytics
Care Providers
Integration
& Quality
Patient Member
Patient Member
Smartphone
Real-Time
Event
Processing
Visualization
Social Data / Signals
Social Data
Connector
RFID, Patient
Monitoring
Healthcare &
Patient Forums
Master
Data
Mgmt
Member / Provider
Master
DATA
PLATFORM
DISCOVERY
PLATFORM
DATA
WAREHOUSE

26. Unified Data
Architecture
DATA
PLATFORM
DISCOVERY
PLATFORM
DATA
WAREHOUSE
The Intelligent
Data Platform
Role-Based Data Management
Tools
Infrastructure Services
Data Intelligence
Metadata Meets Machine Learning
Data Infrastructure
Vibe ™ Virtual Data Machine
New
Industry-
Leading
Data Lake Infrastructure

27. Data Lake Architecture
Informatica Developers are Now Hadoop Developers
Visual Development Environment
Enterprise
Repositories
MDM
DATA REFINEMENT
PPrroofifliele
Parse
ETL
Cleanse
Match
LOAD
SOURCE
DATA
Batch
Replicate
Stream
Archive
Databases
Files
Servers &
Mainframe
JMS Queue’s
Social
Sensor data
SQL
Apache
Hive
Apache
MapReduce
Apache
Tez
Apache
YARN
1
°
°
°
°
°
°
°
°
°
°
°
°
°
N
HDFS
(Hadoop
Distributed
File
System)
DELIVER
Batch
Services
Events
Topics
DATA
WAREHOUSE

28. How do you plan to staff your Big Data projects?
4 weeks
4 days!
2X performance!
Vs.
Hadoop
Hand-coders
Informatica developers
Choose tools that leverages existing skills so you can quickly
staff Big Data projects

29. How do you adopt and minimize the impact of new
and rapidly changing technologies?
Hadoop
Development
Deployment
Cloud DI Servers Data
Warehouse
Choose a platform and tools that minimize the need to
rebuild your data pipeline as technologies change

30. How long does it take you to deploy Big Data
projects to production?
Time to Deploy
Available
24x7 Scale
Maximize
Reuse
Performance
Automa4cally
Deploy
Easy
to
Maintain Flexible
to
Change
Time to Deploy
Everything you build in the sandbox should be immediately
deployed as enterprise ready production

31. Next Steps
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Try the free Informatica Big Data Edition
60-Day Trial
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Download the Hortonworks Sandbox
http://hortonworks.com/products/hortonworks-sandbox/
Download Teradata Express
Download Aster Express
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