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Revolution Analytics (formerly Revolution Computing) is the leading commercial provider of software & support for the popular open source R statistics language. Revolution R products help make predictive analytics accessible to every type of user & budget.

Executive Roadmap

The R Revolution: Fast, Powerful and Cost-Effective Analytics Technologies Reshaping Business Competition Worldwide

Topline Summary

Numbers drive business and big numbers drive big business. Predictive analytics unlocks the value of big numbers, converting them from sprawling collections of data points into finely honed competitive weapons. The language of predictive analytics is R. This amazingly powerful programming language is poised to make the leap from the laboratory to the marketplace. R is changing the face of business – creating an entirely new era of competition based on fast, powerful and cost-effective analytic technologies.

Revolution Analytics is the leading commercial provider of R software and support. The company’s Revolution R products help make predictive analytics accessible to every type of user and budget.

The Data Challenge

We live in a world that is driven and defined by data. Every moment of every day, huge volumes of data are generated, captured and stored.

Wal-Mart, for example, conducts more than 1 million customer transactions every hour, and sends a steady deluge of information to data warehouses that are already among the largest in the world.

Every five years, the amount of digital data collected increases by a factor of 10. IDC estimates that roughly 1,200 exabytes of digital data will be generated this year (an exabyte is 1,000 petabytes, and a petabyte is 1,000 terabytes).

At the same time, organizations all over the world are recognizing the competitive advantages that are created when data is properly organized, analyzed and managed. Companies across a broad spectrum of industries – including retail, service, manufacturing, pharmaceutical, finance and consumer product goods – are convinced that data represents a new form of capital.

Thanks largely to the many novel ways in which data is gathered, the amount of information collected worldwide now exceeds our capacity to store it. We are truly drowning in data.

Not surprisingly, perhaps, only a tiny fraction of this data is ever put to use. Why? Because most of the tools that were built to analyze large amounts of data are slow, expensive and old. Moreover, they were designed to be used almost exclusively by “quants,” who tend to be highly trained specialists with advanced degrees in statistical analysis.

New Technologies for a New Era

The era of these legacy analytic tools is ending, and a new era is beginning. This new era is marked by analytic solutions that are faster, more cost-effective, more user-friendly and more extensible.

These modern analytic technologies can handle very large volumes of data, at very high speeds. In other words, analytic processes that used to take days to perform can now be accomplished in minutes.

Now imagine the value of this extra speed and capacity. Imagine the value of turning your data into useful information that can be applied in an endless variety of practical ways, quickly and cost-effectively. Imagine the value of sifting through mountains of information and gleaning the knowledge you really need to make better decisions.

Welcome to the World of R

The newer, faster and more powerful technologies that make it possible to find needles of insight in haystacks of data are based on an opensource programming language called R.

With more than two million users, R has become the de facto standard platform for statistical analysis in the academic, scientific and analytic communities. If you are taking a statistics class at a college or university, if you are conducting research in applied or theoretical statistics, if you are part of the data management team at a large global organization – chances are good that you are already developing programs using R.

The adoption of R as the lingua franca of analytic statistics is creating a deep pool of fresh talent. Among students, scientists, programmers, and data managers, R is the accepted standard. In a very real sense, R represents both the present and the future of statistical analytics.

Revolutionary Products for Revolutionary Times

Founded in 2007, Revolution Analytics provides commercial software and services that support users of the open-source R statistics language. As the popularity of R grows, Revolution Analytics is positioned to be the premier supplier of powerful, full-featured products for every type of user and every budget.

For the open source user, the company offers Revolution R, a free distribution of the R programming language that has been enhanced for faster performance and greater stability. It is a perfect product for learning R and performing basic analysis. The benefits of Revolution R include:

  • Improved Performance: Optimized libraries and compiler techniques run most computation-intensive programs significantly
    faster than Base R.
  • Greater Reliability: Revolution R is built upon the latest proven & stable R releases.
  • More powerful: Revolution R enables users to leverage the processing power of multi-core processors.
  • Up-to-Date: A constant check of the R project means critical bugs and fixes are incorporated – less for users to worry about.

For large-scale research and real-world business, Revolution Analytics offers Revolution R Enterprise, a premium production-grade analytic platform. The company also offers this same software to the academic community for free – to ensure that professors, students and educational researchers can learn and leverage high-performance, high-productivity R.

Revolution R Enterprise is designed for corporations, government agencies and academic researchers that require the highest levels of performance, reliability and computational power for their large-scale data analysis. It is optimized to run the fastest computations of any R software on a wide-range of platforms – and features a visual development environment that leaves the command-line far behind. A subscription to Revolution R Enterprise also includes direct access to the company’s expert technical support team.

The benefits of Revolution R Enterprise include:

  • Enhanced Speed and Reliability: Revolution R Enterprise is fast, usable and practical, making it the ideal choice for real-world data
    analytics.
  • Visual Productivity: Graphic IDE enables faster, more accurate R programming
  • Visual Debugging: Create reliable R applications faster. Create a breakpoint and step through code with a single click.
  • 64-Bit Scalability: Analyze larger data sets on 64-bit Windows, taking full advantage of your equipment's RAM.
  • Wide Platform Support: Available for 32-bit and 64-bit Windows and Red Hat Enterprise Linux.
  • Parallel Processing Power: Significantly reduce computation time for simulations, optimizations, segmented data analysis and more.
  • On-Call Technical Support: Revolution Analytics is there to support you when you need help or confront an issue.

Revolution Analytics also offers professional training and consulting services to meet specific needs. In the near future, the company will also provide “Big Data” analysis for terabyte-class file structures, integrated web services and a GUI for comprehensive data analysis.

Looking ahead

In 2010, Revolution Analytics will be delivering a series of technologies that will firmly establish its leadership role in the advanced analytics space – pushing R past what is available in legacy tools. Among these capabilities:

  • Big Data Analysis for Terabyte-Class File Structures – A total solution that combines the use of external memory algorithms, distributed parallel computing, high performance data access and an extensible framework for processing huge datasets in R. The compressed file structure and other features are designed to make many R packages run faster and use less memory – thus vastly increasing overall performance. Additionally, it will include a collection of the most-common statistical procedures used on Big Data that are scalable across cores and computers, and are orders of magnitude faster than using legacy tools.
  • Integrated Web Services – A scalable programming platform used to deliver R functionality on the Web and Cloud. It will help enterprises share data and analysis between users, data sources, and other enterprise software -- such as BI tools. Will support both anonymous R Script execution, and authenticated users working in a stateful environment.
  • Comprehensive Data Analysis GUI – A Web-based user interface that radically improves the usability of R, accelerates productivity and enables rapid learning for both novice and experts. Users will be able to seamlessly transition back and forth between R code and dialogs, and be exposed to only as much R code as they want to see. Built on a fully-extensible framework that allows for creating and modifying UI elements (menus, dialogs, outputs), users will be able to customize and extend the UI for their needs.
  • Products and Services to help migrate data and applications from legacy statistical systems to R – such as the ability to import and read SAS, SPSS, and Stata files in an Enterprise R environment, and to convert code written in such systems to the R language.

Revolution R Will Spread Virally

Unlike other programming languages used to crunch large data sets, R is not inextricably tied to any single proprietary system or solution. R presents a truly special opportunity for multiple audiences to partner in the ongoing development of many new software products and services.

The popularity and flexibility of R creates a unique advantage for Revolution R, enabling it to spread virally across the analytics landscape. Revolution R is a textbook case of a disruptive technology that ushers in a new era of radical change and sweeping transformation across the length and breadth of the global economy.

Upsides, Downsides

Because the R programming language is an open-source project, it evolves continually through the contributions of a global community of academics, quantitative analysts and data miners. The evolutionary qualities of R invite comparisons to the early days of Linux, arguably the world’s most famous and most successful open-source project.

This changeable aspect of R can be perceived as a positive and as a negative. On one hand, R is constantly being improved and enhanced by a self-organizing global community of software developers, most of whom contribute their time and energy freely to the project.

On the other hand, no one is officially “in charge” of these developers – if an enhancement proves beneficial, it’s accepted by the community and becomes part of the R language. If an enhancement doesn’t work or if it creates issues that cannot be easily resolved, word spreads through the community and some sort of resolution emerges. In theory, that’s how an open-source project works.

While this kind of arrangement offers some genuinely spectacular benefits – the world’s best programmers collaborating in an unfettered environment of intellectual freedom – it also presents some notable downsides. For example, if you run a business that depends on software written in R to crunch through large data sets, there’s no help desk to call when something goes wrong.

A “Perfect Storm” is Transforming the Industry

A “perfect storm” of events is now pushing R beyond its original core audience of students, scientists and quantitative analysts, and transforming the analytics industry. Revolution Analytics plays a leadership role in supporting and enabling this truly global sea change.

To fully comprehend the extent of this transformation, it is important to look at the conditions and drivers behind it.

The first driver is the aforementioned data deluge, and the consensus that those companies who will succeed in the competitive marketplace are those that can most effectively gain insight and predictions from the data they’ve collected through the use of predictive models.

The second driver is the fact that the application of predictive models to data is no longer a “secret art”; in universities and colleges worldwide, a new generation of data analysts has been trained not just in the necessity of data analysis in today’s business, but in the analytic methods that offer competitive advantage. And the training tool of choice for the vast majority of those students is the R language.

Finally, the economic opportunity is unmistakable: the market for data management and analytic technologies currently generates about $100 billion and is growing at a pace of 10 percent annually. The market leaders in data analysis software today are based on decades-old technology unable to meet current demands for analysis of huge data sets within an easy-to-use user interface. With its modern roadmap centered around the open-source R project, Revolution Analytics stands to significantly disrupt this market.

Overcoming Obstacles to Adoption

As mentioned earlier, open-source software development models offer many benefits – and pose many challenges. The benefits include faster development cycles and lower development costs; the challenges include lack of controls, lack of clear accountability and lack of support.

For many businesses, especially those operating in complex or highly regulated markets, open-source software can be impractical or threatening.

The commercial potential of R, however, has led to a surge of interest in developing enhanced “enterprise grade” versions of R software. These newer applications address the key issues that have prevented R from realizing its full potential as a mainstream enterprise technology.

The two primary obstacles facing many R users today involve capacity and performance.

For example, most R software cannot currently handle the kind of enormous data sets that are generated routinely by large multi-channel
retailers, consumer packaged good marketers, pharmaceutical companies, global finance organizations or national government agencies. The capacity of R-based solutions is limited by the requirement that all the data has to fit in memory in order to be processed. The algorithms simply won’t scale to accommodate “Big Data,” the phrase that describes exploding data sets that are, in traditional terms, too large to analyze.

This capacity limitation then forces analysts to use smaller samples of data, which can lead to inaccurate or sub-optimal results.

The second issue involves the inability of many R applications to read data quickly from files or other sources. Speed is critical in all areas of modern life, and it seems unreasonable to wait weeks or months for a computer to crunch through larger sets of data.

Although some software packages claim to address these issues, what’s usually missing is an over-arching framework with a top-down approach for analyzing “Big Data” easily and efficiently. Typically, analysts find themselves struggling with a collection of software tools that can create more problems than they solve.

Revolution Analytics addresses these critical issues head on – and solves them.

Speed, Power and More

Revolution Analytics overcomes the capacity problem through a proprietary external memory framework. The external memory framework enables extremely fast chunking of data from large data sets, which typically include billions of rows and thousands of columns.

But even the fastest data processing can take hours if it is performed sequentially. Overcoming this performance obstacle requires the capability to distribute computations automatically among multiple cores and multiple computers through the use of parallel external memory algorithms.

For example, a computer with four cores can perform analytic calculations very quickly because one core reads the data while the other three cores process the data. Performance can be improved even more dramatically by distributing the work across a network of computers, reducing processing time from hours to minutes or mere seconds.

But the quest for speed doesn’t stop there. Revolution Analytics has also developed a proprietary high performance process that enables users to select specific rows and columns to read within the data file. This process represents a significant advancement in speed and efficiency over earlier R packages that required reading the entire data file before handling a specific piece of data.

Houston, We Have a Problem

Anyone who has ever worked under deadline pressure knows that even the most robust technology can fail precisely when you need it the most.

As R moves from colleges and universities into larger-scale environments, real world and becomes the foundation of a new generation of analytic platforms, the availability of 24x7 support and other professional services will become imperative. Like many open-source projects, R has no “command center” to call when things go wrong. Nor is there a “central authority” working to ensure consistency and compatibility across the various builds and versions of R.

Revolution Analytics, however, understands the real needs of largescale users, and offers the types of support and services that have become standard across the software solutions community.

The New Normal

The R revolution is just beginning. As it spreads, it will transform business at every level. The idea of making critical decisions based on hunches or intuition will seem hopelessly antiquated. It will become common practice for business leaders to rely on knowledge generated through rigorous numerical analysis of large data sets. Fact-based decision making will become the norm instead of the exception.

The use of “Big Data” to guide business decisions – at every level of the enterprise – will become practical, affordable and commonplace. At the same time, more organizations will depend more heavily on data analysis to generate competitive advantages. The intersection of these trends – user-friendly, cost effective analytics and growing reliance on larger data sets to fuel decision-making processes – will have a profound impact on the economy and upon the broader culture.

As an innovative leader, developer and supplier of critical new software and services, Revolution Analytics will play a significant role in this transformation.

Concluding Summary Points

  • With more than two million users, R has become the de facto standard platform for statistical analysis in the academic, scientific and analytic communities.
  • A “perfect storm” of events is now pushing R beyond its original core audience and transforming the analytics industry.
  • Revolution Analytics plays a leadership role in supporting and enabling this truly global sea change.
  • Revolution R will spread virally.
  • Revolution R is a textbook case of a disruptive technology that ushers in a new era of radical change.
  • Revolution Analytics provides commercial software and services that support users of the open-source R programming language.
  • This year, Revolution Analytics will deliver a series of technologies that will firmly establish its leadership role in the advanced analytics space – pushing R past what is available in legacy tools.
  • As the popularity of R grows, Revolution Analytics is positioned to be the premier supplier of powerful, full-featured products for every type of user and every budget.

About Revolution Analytics

Revolution Analytics (formerly Revolution Computing) was founded in 2007 to foster the R Community, as well as support the growing needs of commercial users. Through our Revolution R products, we aim to make the power of predictive analytics accessible to every type of user & budget. We provide free and premium software and services that bring high-performance, productivity and ease-of-use to R – enabling statisticians and scientists to derive greater meaning from large sets of critical data in record time.

We also offer our full-featured production-grade software to the academic community at no cost, in order to support the continued spread of R's popularity to the next generation of analysts.

For customers such as Pfizer, Novartis, Yale Cancer Center, Bank of America, Motorola, Hess and others, our flagship Revolution R Enterprise product is designed to deliver faster drug development, reduced time of data analysis, and more powerful and efficient financial models.

Revolution Analytics' executive leadership represents some of the most respected and experienced names in statistical computing and open-source business – with venture funding from Intel Capital and North Bridge Venture Partners.

For more information

Contactasymptotix JAM sept 10

John Morrison
CIO, Asymptotix
Tel: +32 475 63 2991