[September 06, 2012]

Big Data and High-Performance Analytics focus for SAS at Disney Analytics Summit

There's a lot of talk about the "new" challenge of Big Data. It seems every organization either has Big Data or is getting it. But what's actually new here And where does true value emerge from Big Data For SAS (News - Alert), the leader in advanced analytics (per IDC), the answer is clear: Analytics.

"It's not the size of the data that matters. It's what you do with it, and that's where analytics are key," said Randy Guard, Vice President of Sales Development and Product Management at SAS.

Within sight of the Magic Kingdom's iconic fairy-tale Cinderella Castle, Guard and SAS Vice President of Advanced Analytics R&D Radhika Kulkarni presented on trends in Big Data Analytics at the 12^th annual Disney (News - Alert) Analytics & Optimization Summit. The Walt Disney Company (NYSE: DIS) hosted the Summit last week (Aug. 29-30^th) in Lake Buena Vista, Fla.

Per its Web site, The Disney Analytics and Optimization Summit 2012 "brings together some of the most talented analytical Cast Members within The Walt Disney Company to share best practices and learning in the areas of Measurement, Forecasting, Optimization, and Pricing." The Summit was also open to analytical professionals from around the world. SAS was a platinum sponsor of the event.

"For organizations like Disney, analytics are part of the corporate DNA," said Cameron Davies, Director of Management Science & Integration for Walt Disney Parks and Resorts. "With analytics, we can make better, faster business decisions that help us improve the overall experience for our customers and guests. Sharing new analytics ideas, approaches and technologies within Disney and with other like-minded organizations is a key goal of our annual Disney Analytics & Optimization Summit."

Big Data: Go Big or Go Home

In their joint presentation "Go Big … or Go Home," SAS' Kulkarni and Guard gave historical perspectives on the growth of data, and discussed new technologies like High-Performance Analytics and advanced visualization that transform huge volumes of data into better, faster business decisions. They introduced the concept of the Analytics Lifecycle, which ranges from data analysis to modeling and monitoring. And they shared best practices for attracting and keeping analytical talent, including data scientists, statisticians and analysts.

"However you define it, Big Data is here to stay and data volumes will continue to expand," said Kulkarni. "Big Data underscores the real need for a scalable and reliable analytics infrastructure to support data analysis and modeling."

Also speaking at the Disney Summit were SAS Solutions OnDemand Director of Analytic Business Development Tom Lehman and Social Media Analyst Jody Porowski. SAS Solutions OnDemand are software-as-a-service (SaaS (News - Alert)) and enterprise hosted solutions based on SAS' industry-leading business analytics.

Lehman and Porowski discussed mood state analysis, a new method for analyzing unstructured data from Twitter (News - Alert), Facebook and other social media channels to quickly reveal customer mood and intent. Mood state analysis can help organizations discover areas that need attention so they can take steps to improve the customer's emotional state, and the overall customer experience.

About SAS

SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 60,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW^®.

SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2012 SAS Institute Inc. All rights reserved.

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