Real-time Big Data Analytics: From Deployment to Production
|Presented:||Thursday, November 29, 2012|
|Presenter:||David Smith, VP Marketing & Community
|Downloads:||Download the webinar presentation and replay.|
As the Big Data market has evolved, the focus has shifted from data operations (storage, access and processing of data) to data science (understanding, analyzing and forecasting from data). And as new models are developed, organizations need a process for deploying analytics from research into the production environment. In this talk, we'll describe the five stages of real-time analytics deployment:
- Data distillation
- Model development
- Model validation and deployment
- Model refresh
- Real-time model scoring
We'll review the technologies supporting each stage, and how Revolution Analytics software works with the entire analytics stack to bring Big Data analytics to real-time production environments.
About the Speaker
David Smith is the Vice President of Marketing and Community at Revolution Analytics, the leading provider of software and services for the open-source R statistical language. David writes daily about applications of R, analytics and open-source software at the Revolutions blog (blog.revolutionanalytics.com), and was named a top 10 influencer on the topic of “Big Data” by Forbes. He is the co-author (with Bill Venables) of the tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Prior to joining Revolution Analytics, David was the director of product management for S-PLUS at Insightful, Inc. Follow David on Twitter as @revodavid.