The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full November edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Now Available: Revolution R Enterprise 6.1 The latest release of Revolution Analytics' enterprise-ready data...
202 search results for "hadoop"
Webinar Tomorrow: Big Data Trees and Hadoop Connection in Revolution R Enterprise 6.1
Tomorrow at 9AM Pacific, Revolution Analytics VP of Product Development Sue Ranney will introduce two key Big Data features of the new Revolution R Enterprise 6.1. Now you can train classification and regression trees on data sets of unlimited size, quickly and using the resources of multiple processors and clusters. (This white paper describes our implementation of tree models...
Big Data ETL and Big Data Analysis
I was at Strata New York 2012 last month. Great conference! Thanks O'Reilly media for assembling the industry leaders and running it well.I understand it was too crowded for some of my out-of-town friends. Stepping out to the streets of mid-town Manhat...
Benchmarking bigglm
By Joseph Rickert In a recent blog post, David Smith reported on a talk that Steve Yun and I gave at STRATA in NYC about building and benchmarking Poisson GLM models on various platforms. The results presented showed that the rxGlm function from Revolution Analytics’ RevoScaleR package running on a five node cluster outperformed a Map Reduce/ Hadoop implementation...
What’s new in Revolution R Enterprise 6.1
We're pleased to announce that the latest update to Revolution R Enterprise is available today! Existing subscribers will soon receive an email with update instructions, and the free academic distribution will be updated later today. Version 6.1 adds a frequently-requested big-data statistical modeling algorithm, adds new connectivity option for Hadoop, improves performance, and provides new security and installation options...
In case you missed it: October 2012 Roundup
In case you missed them, here are some articles from October of particular interest to R users. Sponsorships for local R user groups from Revolution Analytics are now open to applicants worldwide. During the landfall of Hurricane Sandy in the US, several R-based apps used public weather and social media data to document its impact, like this timeline of...
R among TechCrunch’s 5 Trendy Open-Source Techs for Big Data
Tim Gasper (Product Manager at Big Data platform Infochimps) has an informative article at TechCrunch that provides an overview of five open-source technologies trending now for Big Data applications. They are: Storm and Kafka (for processing stream data) Drill and Dremel (for ad-hoc queries of big data) R (for data science with big data) Gremlin and Giraph (for graph...
Allstate compares SAS, Hadoop and R for Big-Data Insurance Models
At the Strata conference in New York today, Steve Yun (Principal Predictive Modeler at Allstate's Research and Planning Center) described the various ways he tackled the problem of fitting a generalized linear model to 150M records of insurance data. He evaluated several approaches: Proc GENMOD in SAS Installing a Hadoop cluster Using open-source R (both on the full data...
Quick notes from Strata NYC 2012
The O'Reilly Strata conferences are always great fun to attend, and this latest installment in New York City is no exception. This one is super-busy though; the conference has been sold out for weeks -- and not just marketing-sold-out, it's fire-department-sold out. It's non-stop conversations and presentations, and it's tough to move through the hallways in between. Nonetheless, I...
Two Talks on Data Science, Big Data and R
On Thursday next week (November 1), I'll be giving a new webinar on the topic of Big Data, Data Science and R. Titled "The Rise of Data Science in the Age of Big Data Analytics: Why Data Distillation and Machine Learning Aren’t Enough", this is a provocative look at why data scientists cannot be replaced by technology, and why...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
