Announcing: Release 7

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Benedict Daniels
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1 Announcing: Release 7 Revolution R Enterprise Tuesday, November 5 Michele Chambers, Chief Strategy Officer and VP Product Management Thomas W. Dinsmore, Director of Product Management

2 Agenda Introduction Demystifying R Revolution Analytics at a Glance Revolution R Enterprise Revolution Analytics Partner Ecosystem Customer Testimonials What s New in RRE 7? More Information Questions 2

3 Demystifying R What is R & why is it so darn popular?

email discussion list R Package Growth Number

2013 Stata SAS SPSS S-Plus Web Site Popularity

S-Plus Stata Scholarly Activity Google Scholar

4 R is exploding in popularity & function Internet Discussion Mean monthly traffic on discussion list R Package Growth Number of R packages listed on CRAN 4,332 as of Feb 2013 Stata SAS SPSS S-Plus Web Site Popularity Number of links to main web site R SAS SPSS S-Plus Stata Scholarly Activity Google Scholar hits ( CAGR) R 46% SAS -11% SPSS -27% S-Plus 0% Stata 10% 4

Latest survey shows significant growth in R adoption R Usage Growth Rexer Data Miner Survey, 2007-2013 70% of data miners report using R I ve been astonished by the rate at which R has been

Deputy Editor for New Products at Forbes 24% use R as primary tool Source: www.rexeranalytics.

5 Latest survey shows significant growth in R adoption R Usage Growth Rexer Data Miner Survey, % of data miners report using R I ve been astonished by the rate at which R has been adopted. Four years ago, everyone in my economics department [at the University of Chicago] was using Stata; now, as far as I can tell, R is the standard tool, and students learn it first. Deputy Editor for New Products at Forbes 24% use R as primary tool Source: A key benefit of R is that it provides near-instant availability of new and experimental methods created by its user base without waiting for the development/release cycle of commercial software. SAS recognizes the value of R to our customer base Product Marketing Manager SAS Institute, Inc 5

6 Revolution Analytics at a Glance Who We Are Only provider of commercial big data big analytics platform based on open source R statistical computing language Our Software Delivers Scalable Performance: Distributed & parallelized analytics Cross Platform: Write once, deploy anywhere Productivity: Easily build & deploy with latest modern analytics Our Services Deliver Knowledge: Our experts enable you to be experts Time-to-Value: Our Quickstart program gives you a jumpstart Guidance: Our customer support team is here to help you Customers 200+ Global 2000 Global Presence North America / EMEA / APAC Global Industries Served Financial Services Digital Media Government Health & Life Sciences High Tech Manufacturing Retail Telco 6

7 Revolution R Enterprise is. the only big data big analytics platform based on open source R the defacto statistical computing language for modern analytics High Performance, Scalable Analytics Portable Across Enterprise Platforms Easier to Build & Deploy Analytics 7

8 R is open source and drives analytic innovation but.has some limitations for Enterprises Big Data In-memory bound Hybrid memory & disk scalability Speed of Analysis Enterprise Readiness Analytic Breadth & Depth Commercial Viability Operates on bigger volumes & factors Single threaded Parallel threading Shrinks analysis time Community support Commercial support Delivers full service production support innovative analytic packages Risk of deployment of open source Leverage open source packages plus Big Data ready packages Commercial license Supercharges R Eliminate risk with open source 8

9 Introducing Revolution R Enterprise (RRE) The Big Data Big Analytics Platform DevelopR ConnectR ScaleR DistributedR DeployR Big Data Big Analytics Ready Enterprise readiness High performance analytics Multi-platform architecture Data source integration Development tools Deployment tools 9

10 The Platform Step by Step: R Capabilities R+CRAN Open source R interpreter Freely-available R algorithms Algorithms callable by RevoR Embeddable in R scripts 100% Compatible with existing R scripts, functions and packages RevoR Performance enhanced R interpreter Based on open source R Adds high-performance math 10

11 The Platform Step by Step: Parallelization & Data Sourcing ConnectR High-speed & direct connectors ScaleR Ready-to-Use high-performance big data big analytics Fully-parallelized analytics Data prep & data distillation Descriptive statistics & statistical tests Correlation & covariance matrices Predictive Models linear, logistic, GLM Machine learning Monte Carlo simulation Tools for distributing customized algorithms across nodes DistributedR Distributed computing framework Delivers portability across platforms 11

12 The Platform Step by Step: Tools & Deployment DevelopR Integrated development environment for R Visual step-into debugger DevelopR DeployR DeployR Web services software development kit for integration analytics via Java, JavaScript or.net APIs Integrates R Into application infrastructures Capabilities: Invokes R Scripts from web services calls RESTful interface for easy integration Works with web & mobile apps, leading BI & Visualization tools and business rules engines 12

13 Write Once. Deploy Anywhere. Hadoop Hortonworks Cloudera EDW IBM Netezza Teradata ConnectR DeployR Clustered Systems Workstations & Servers IBM Platform LSF Microsoft HPC Desktop Server ScaleR DistributedR In the Cloud Microsoft Azure Burst Amazon AWS DESIGNED FOR SCALE, PORTABILITY & PERFORMANCE 13

14 The Power of Revolution R Enterprise Performance & Scalability V a l u e ScaleR ScaleR ScaleR ScaleR DistributedR DistributedR DistributedR RevoR Open Source Moves computation to data Moves computation to data Leverage CRAN Labor saving power Maximizes computation Powerful divide & conquer Effective memory utilization 3-50X faster Leverage latest innovation 14

15 Revolution R Enterprise Powering Next Generation Analytics COMBINE INTERMEDIATE RESULTS 15

Revolution R Enterprise Revo R Performance Enhanced R Open Source R Customers report Revolution 3-50x R

laptop) Open Source R Revolution R Speedup Linear Algebra 1 Matrix Multiply 176 sec 9.

3 sec 19x Linear Discriminant Analysis 189 sec 74 sec 3x General R Benchmarks 2 R Benchmarks (Matrix

16 Revolution R Enterprise Revo R Performance Enhanced R Open Source R Customers report Revolution 3-50x R performance improvements Enterprise compared to Open Source R without changing any code Computation (4-core laptop) Open Source R Revolution R Speedup Linear Algebra 1 Matrix Multiply 176 sec 9.3 sec 18x Cholesky Factorization 25.5 sec 1.3 sec 19x Linear Discriminant Analysis 189 sec 74 sec 3x General R Benchmarks 2 R Benchmarks (Matrix Functions) 22 sec 3.5 sec 5x R Benchmarks (Program Control) 5.6 sec 5.4 sec Not appreciable

17 RRE ScaleR outperforms SAS HPA at a fraction of the cost Logistic Regression: Rows of data 1 billion 1 billion Parameters just a few Double 7 Time 80 seconds 45% 44 seconds Data location In memory On disk Nodes 32 1/6 th 5 Cores 384 5% 20 RAM 1,536 GB 5% 80 GB Revolution R is faster on the same amount of data, despite using approximately a 20 th as many cores, a 20 th as much RAM, a 6 th 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,

18 R + Revolution R Enterprise Unequaled Big Data Big Analytics Deploy Analytics Web, Mobile, Data Visualization, BI Big Data Distributed Analytics Big Data Distributed Analytics Performance Enhanced R Performance Enhanced R 18

19 Revolution R Enterprise Ecosystem Power of Integration SI / Service Deployment / Consumption MSP / DSP Advanced Analytics ETL Corios Data / Infrastructure 19

Customers Revolutionize their Business Power 4X performance 50M records scored daily We ve combined Revolution R Enterprise and Hadoop to build and deploy customized exploratory data analysis and GAM

Given that our data sets are already in the terabytes and are growing rapidly, we depend on Revolution R Enterprise s scalability and power we saw about a 4x performance improvement on 50 million

20 Customers Revolutionize their Business Power 4X performance 50M records scored daily We ve combined Revolution R Enterprise and Hadoop to build and deploy customized exploratory data analysis and GAM survival models for our marketing performance management and attribution platform. Given that our data sets are already in the terabytes and are growing rapidly, we depend on Revolution R Enterprise s scalability and power we saw about a 4x performance improvement on 50 million records. It works brilliantly. - CEO, John Wallace, DataSong Scalability TB s data from 200+ data sources 10 s thousands attributes 100 s millions of scores daily We ve been able to scale our solution to a problem that s so big that most companies could not address it. If we had to go with a different solution we wouldn t be as efficient as we are now. - SVP Analytics, Kevin Lyons, exelate Performance 2X data 2X attributes no impact on performance We need a high-performance analytics infrastructure because marketing optimization is a lot like a financial trading. By watching the market constantly for data or market condition updates, we can now identify opportunities for our clients that would otherwise be lost. - Chief Analytics Officer, Leon Zemel, [x+1] 20

21 What s New in RRE 7

22 The Power of R Most widely used analytics tool Preferred by working analysts More than 6,000 packages Global footprint New R

23 Scalable Statistical Modeling Linear Regression Stepwise Linear Logistic Regression Generalized Linear Models New Stepwise Logistic Stepwise GLM 23

24 Scalable Machine Learning Decision Trees New Decision Forests Tree Visualization 24

25 Data Source Integration Fixed/delimited text SAS, SPSS ODBC HDFS and HBase Teradata Tested HP Vertica Teradata Aster 25

26 New: Model Integration 26

27 BI Integration Custom web reports QlikView accelerator New Excel Accelerator Tableau Integration 27

28 New: Business User Interface 28

29 Choice of Operating Systems 29

30 New: Inside-Hadoop Deployment 30

31 Multi-Node Package Manager HDFS Name Node MapReduce Data Node Data Node Data Node Data Node Data Node Task Tracker Task Tracker Task Tracker Task Tracker Task Tracker Job Tracker 31

32 ScaleR in Hadoop HDFS Name Node MapReduce Data Node Data Node Data Node Data Node Data Node Task Tracker Task Tracker Task Tracker Task Tracker Task Tracker Job Tracker 32

33 In-Database Deployment 33

34 Summary: What s New in RRE 7.0 R

35 Summary: What s New in RRE 7.0 Stepwise Logistic Stepwise GLM Decision Forests Tree Visualizer PMML Export 35

36 Summary: What s New in RRE

37 Summary: What s New in RRE

38 Summary: What s New in RRE 7.0 DevelopR DeployR 38

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