A 5-minute history

David M SmithChief Community Officer@revodavid

Sponsor Presentation, useR! 2014

2

2007: The Beginning

3

2008: Revolutions Blog

4

R in the News

2009

New York Times:Data Analysts Captivated by R’s Power

5

2009

Revolution R Enterprise

version 3

First R Debugging IDE

6

2010: User Group Sponsorships

141 R User Groups

Rows of data 1 billion 1 billion

Parameters “just a few” 7

Time 80 seconds 44 seconds

Data location In memory On disk

Nodes 32 5

Cores 384 20

RAM 1,536 GB 80 GB

Double

45%

1/6th

5%

5%Revolution R is faster on the same amount of data, despite using approximately a 20 th as many cores, a 20th as much RAM, a 6th as many nodes, and not pre-loading data into RAM.

Bottom Line: Revolution R Enterprise Performance = Greatly Reduced TCO*As published by SAS in HPC Wire, April 21, 2011

Logistic Regression:

7

2010: Head to Head with SAS

8

2011: RHadoop

github.com/RevolutionAnalytics/RHadoop

2012: Clusters, Hadoop and DatabasesWrite Once Deploy Anywhere

rxSetComputeContext("local") # DEFAULT

rxSetComputeContext(RxHadoopMR(<data, server environment arguments>))

# Summarize and calculate descriptive statistics from the data airDS data setadsSummary <- rxSummary(~ArrDelay+CRSDepTime+DayOfWeek, data = airDS)

# Fit Linear Model arrDelayLm1 <- rxLinMod(ArrDelay ~ DayOfWeek, data = airDS); summary(arrDelayLm1)

rxSetComputeContext(RxHpcServer(<data, server environment arguments>))

rxSetComputeContext(RxLsfCluster(<data, server environment arguments>))

Same code to be run anywhere …..

Local System (default)

Set the desired compute context for code execution…..

rxSetComputeContext(RxTeradata(<data, server environment arguments>))

10

2013Shaking up the industryA Gartner Magic QuadrantVisionary

11

2014: Technical Support for Open Source RAdviseR™ from Revolution Analytics

Technical support for open source R, from the R experts.

10x5 email and phone support Support for R, validated packages, and third-party software

connections On-line case management and knowledgebase Access to technical resources, documentation and user forums Exclusive on-line webinars from community experts Guaranteed response times

Also available: expert hands-on and on-line training for R, from Revolution Analytics AcademyR.

www.revolutionanalytics.com/AdviseRwww.revolutionanalytics.com/AcademyR

R SUPPORT12 MONTHS

$795PER USER

… and beyond!Continued growth and demand for R

R is the highest paid IT skill– Dice.com, Jan 2014

R most-used data science language after SQL– O’Reilly, Jan 2014

R is used by 70% of data miners– Rexer, Sep 2013

R is #15 of all programming languages– RedMonk, Jan 2014

R growing faster than any other data science language

– KDnuggets, Aug 2013 More than 2 million users worldwide

R Usage GrowthRexer Data Miner Survey, 2007-2013

70% of data miners report using R

R is the first choice of moredata miners than any other software

Source: www.rexeranalytics.com

Thank youRevolution Analytics is the leading commercial provider of software and support for the popular open source R statistics language.

www.revolutionanalytics.com, 1.855.GET.REVO, Twitter: @RevolutionR

13