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Explaining real-time predictive analytics with big data (video)

In my presentation to the Strata Santa Clara 2013 conference earlier this year, my goal was to give a succinct (under 20 minutes!) explanation of three terms that are two often used as mere buzzwords: predictive analytics, real time, and big data.   You can download the slides for my presentation, Real-time Big Data Analytics: From Deployment to Production, from SlideShare. In the talk I referenced the example UpStream Software's marketing attribution model. Last week I posted some details of how they used R to create and deploy the model for clients like Williams Sonoma, so follow that link if you're interested in the details. I didn't have much time to get into why I believe that the R language is the ideal environment for creating such models, but I go into more depth in this longer version of the presentation.

Read the original blog entry...

More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

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