1. Lowering the entry point to getting going with Hadoop and obtaining business VALUE

2. Almost 4 decades of Advanced Analytics & DM expertise.
SAS & Hadoop
Who is SAS?
Almost 4 decades of Advanced Analytics & DM expertise.
Validated by Gartner and Forrester Analysts as Leaders in Advanced Analytics, BI and DM.
Leader in *17* Gartner’s Magic Quadrants from Data Management, BI to Advanced Analytics.
400 offices, 70,000+ customers, 135 countries with largest ecosystem of users and partners.
38% of Advanced Analytics Market Share (per IDC).
25% reinvested into R&D.

3. Gartner: Magic Quadrant For Advanced analytic Platforms
Gartner defines advanced analytics as, "the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover."
Gartner Magic Quadrant for Advanced Analytics Platforms by Gareth Herschel, Alexander Linden, Lisa Kart, 19 February 2015.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SAS. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Copyright © 2006, SAS Institute Inc. All rights reserved.

4. Primary reason for considering Hadoop Results & Key Findings
SAS & Intel Study
Hadoop Adoption & challenges
Research summary: SAS and Intel asked more than 300 IT-managers from the largest companies in Denmark, Finland, Norway and Sweden about the adoption of Big Data analytics and Hadoop.
Primary reason for considering Hadoop
Results & Key Findings
60% - cited advanced analytics, data discovery, or as an analytical lab
22% - would like to speed up processing
Adoption / Obstacles
35% - cited “Resources and Competencies”

5. This is the issue SAS is tackling head on!

6.    SAS & Hadoop intersect in many ways:
How?
SAS & Hadoop intersect in many ways:
SAS can treat Hadoop just as any other data source, pulling data FROM Hadoop, when it is most convenient;
SAS can work WITH Hadoop, lifting data in a purpose-built advanced analytics in-memory environment;
SAS can work directly IN Hadoop, leveraging the distributed processing capabilities of Hadoop.   

7. Use the right approach for what needs to be done!
SAS & Hadoop
The pragmatic Approach
Move data FROM Hadoop into a SAS environment
Prepare data IN Hadoop for analytics
MANAGE DATA
EXPLORE
DATA
DEVELOP MODELS
DEPLOY &
MONITOR
Use the right approach for what needs to be done!
Explore data in-memory WITH data visualization and approachable modelling
Deploy and manage model score code IN Hadoop
Model data in-memory WITH advanced modeling tools
Lift data IN to memory for analytics

8. Demo Sector: Online e-commerce shop
Business Problem: Having difficulty to keep profitable customers returning to the web site
Specific aim: Identify the reasons for clients to abandon their shopping cart and predict those visitors with a high probability to abandon
Challenge: Getting big data stored into Hadoop and accessing it is difficult for analysts to access from their traditional systems without specific expertise
Demo

9. ENABLING ENTIRE ANALYTICS LIFECYCLE AROUND HADOOP
TEXT
MANAGE DATA
EXPLORE
DATA
DEVELOP MODELS
DEPLOY &
MONITOR
SAS/ACCESS to Hadoop
SAS Data Loader for Hadoop
SAS Data Management
SAS Federation Server
SAS Event Stream Processing
SAS Visual Analytics
SAS In-memory Statistics
SAS Visual Statistics
SAS Scoring Accelerator for Hadoop
SAS High-Performance Analytics Products

10. Supporting the entire analytics journey! Why SAS?
SAS® Visual Analytics
SAS® Visual Statistics
SAS® In-Memory Statistics
SAS® Enterprise Miner / SAS® Forecast Server
SAS® Decision Manager / SAS® Scoring Accelerator
Supporting the entire analytics journey!
Why SAS?
Capabilities to deploy, monitor and automate analytics with appropriate business rules into operational business processes
Robust production modelling tools that provide for repeatability and easy operationalization
State-of-the-art interactive analytics driven through a programmatic interface
In-depth GUI driven approachable modelling
Data exploration, analysis, visualization and approachable analytics for the masses
SAS® Data Loader for Hadoop
Visualize, explore, interact, explain, understand, democratize
Finalize, Deploy, integrate, execute, operationalize, industrialize

11. SAS and Hadoop
summary
SAS is the only vendor to work FROM + WITH + IN Hadoop throughout the analytics lifecycle.
All three approaches can be combined and coordinated, complementing each other for each situation.
Each approach can evolve, mature and/or morph into the other.
SAS can help realize the value of Hadoop; bring production-analytics to the platform.

12. Thank you Mark.Torr@sas.com
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