A 5-minute history
David M Smith
Chief Community Officer
@revodavid
Sponsor Presentation, useR! 2014
2
2007: The Beginning
3
2008: Revolutions Blog
R in the News
2009
New York Times:
Data Analysts
Captivated by R’s
Power
4
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
Node...
8
2011: RHadoop
github.com/RevolutionAnalytics/RHadoop
2012: Clusters, Hadoop and Databases
Write Once  Deploy Anywhere
rxSetComputeContext("local") # DEFAULT
rxSetComputeConte...
10
2013
Shaking up the
industry
A Gartner Magic Quadrant
Visionary
11
2014: Technical Support for Open Source R
AdviseR™ from Revolution Analytics
Technical support for open source R, from ...
… and beyond!
Continued growth and demand for R
 R is the highest paid IT skill
– Dice.com, Jan 2014
 R most-used data s...
Thank you
Revolution Analytics is the leading commercial
provider of software and support for the
popular open source R st...
Upcoming SlideShare
Loading in...5
×

Revolution Analytics: a 5-minute history

7,307

Published on

Revolution Analytics was the first company dedicated to the R Project. This presentation from useR! 2014 covers the history of Revolution Analytics since its founding in 2007 and its contributions to the R project and community.

Published in: Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
7,307
On Slideshare
0
From Embeds
0
Number of Embeds
24
Actions
Shares
0
Downloads
44
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide
  • http://blog.revolutionanalytics.com/2011/01/a-new-sponsorship-program-for-local-r-user-groups.html
  • http://blog.revolutionanalytics.com/2014/02/r-salary-surveys.html
    http://blog.revolutionanalytics.com/2014/01/in-data-scientist-survey-r-is-the-most-used-tool-other-than-databases.html
    http://blog.revolutionanalytics.com/2013/10/r-usage-skyrocketing-rexer-poll.html
    http://blog.revolutionanalytics.com/2014/02/r-is-15th-of-top-programming-languages-in-latest-redmonk-ranking.html
    http://blog.revolutionanalytics.com/2013/09/top-languages-for-data-science.html
  • Revolution Analytics: a 5-minute history

    1. 1. A 5-minute history David M Smith Chief Community Officer @revodavid Sponsor Presentation, useR! 2014
    2. 2. 2 2007: The Beginning
    3. 3. 3 2008: Revolutions Blog
    4. 4. R in the News 2009 New York Times: Data Analysts Captivated by R’s Power 4
    5. 5. 5 2009 Revolution R Enterprise version 3 First R Debugging IDE
    6. 6. 6 2010: User Group Sponsorships 141 R User Groups
    7. 7. 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 20th 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. 8. 8 2011: RHadoop github.com/RevolutionAnalytics/RHadoop
    9. 9. 2012: Clusters, Hadoop and Databases Write Once  Deploy Anywhere rxSetComputeContext("local") # DEFAULT rxSetComputeContext(RxHadoopMR(<data, server environment arguments>)) # Summarize and calculate descriptive statistics from the data airDS data set adsSummary <- 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. 10. 10 2013 Shaking up the industry A Gartner Magic Quadrant Visionary
    11. 11. 11 2014: Technical Support for Open Source R AdviseR™ 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/AdviseR www.revolutionanalytics.com/AcademyR R SUPPORT 12 MONTHS $795 PER USER
    12. 12. … 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 Growth Rexer Data Miner Survey, 2007-2013 70% of data miners report using R R is the first choice of more data miners than any other software Source: www.rexeranalytics.com
    13. 13. Thank you Revolution 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
    1. A particular slide catching your eye?

      Clipping is a handy way to collect important slides you want to go back to later.

    ×