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

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.

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.

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. http://nordichadoopsurvey.com 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”

This is the issue SAS is tackling head on!

   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.   

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

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

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

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

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.

Thank you Mark.Torr@sas.com Lets connect on LinkedIn: http://de.linkedin.com/in/marktorr/en Follow my interests on Twitter: https://twitter.com/mark_torr