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

May 6, 2013

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

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.

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)