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Revolution Analytics to Support In-Hadoop Big Data Predictive Analytics for Cloudera

Revolution R Enterprise 7.0 to Run Within Cloudera CDH3 and CDH4, Providing Powerful Big Data Analytics with Seamless Workflow

Revolution Analytics, the leading commercial provider of software, services and support for the open source R project, today announced it will offer increased support for Hadoop as a platform for Big Data analytics with Cloudera CDH3 and CDH4 in its upcoming release of Revolution R Enterprise 7.0. With Revolution R Enterprise 7.0, the vast library of ScaleR algorithms will provide the easiest and fastest way to build and deploy R-powered Big Data analytics within Cloudera, eliminating data movement latency and speeding results.

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“Hadoop has quickly evolved from a batch-oriented data store to a high-performance, integrated environment that allows organizations to process, visualize and search all kinds of data,” said Charles Zedlewski, vice president, Products, Cloudera. “With Revolution Analytics and the power of R, Cloudera customers will be able to easily build and deploy predictive analytics models. The convergence of R and Hadoop is a powerful advancement.”

Revolution Analytics’ partnership with Cloudera supports its commitment to provide enterprises with the flexibility to leverage R-enabled analytics with the data infrastructure platform of their choice. Revolution R Enterprise 6.2, currently available, is certified to work with Cloudera CDH3 and CDH4, allowing researchers to write their own Hadoop-based analytics in R and deploy them within the Cloudera environment. With Revolution R Enterprise 7.0, Cloudera customers will have the ability to quickly and easily invoke R-powered predictive models, and push beyond simple summaries, queries and data visualization to produce game-changing insights from data managed by the Hadoop environment. This can all be achieved without having to learn to write MapReduce in Java, Python or other languages, without using SQL and without having to know how to design parallel algorithms. 

Cloudera customers will be able to take on Big Data analytics initiatives with Revolution R Enterprise. Revolution Analytics in-database analytics offers:

  • Accelerated model development cycle times by eliminating data movement latency; and
  • More complete, speedy results because the entire data set may be included in analysis at once, which is critical for any applications that detect outliers, such as to detect fraudulent claims or trades, or applications that score the entire data set, such as customer analytics, machine or sensor data analytics, or credit worthiness.

“Revolution Analytics is devoted to creating an ecosystem that connects existing data management technologies and platforms with the power of modern, R-based predictive analytics,” said Dave Rich, CEO of Revolution Analytics. “This new offering with Cloudera does just that: delivering customers the power, scale, economy and innovation they need to grow more quickly and work more efficiently.”

About Revolution Analytics

Revolution Analytics is the leading commercial provider of software and services based on the open source R project for statistical computing. The company brings high performance, productivity and enterprise readiness to R, the most powerful statistics language in the world. The company’s flagship Revolution R Enterprise product is designed to meet the production needs of large organizations in industries such as finance, life sciences, retail, manufacturing and media. Used by over two million analysts in academia and at cutting-edge companies such as Google, Bank of America and Acxiom, R has emerged as the standard of innovation in statistical analysis. Revolution Analytics is committed to fostering the continued growth of the R community through sponsorship of the Inside-R.org community site, funding worldwide R user groups and offering free licenses of Revolution R Enterprise to everyone in academia.

Media Contact

Jill Reed or Angela Lestar
Schwartz MSL
Phone: (415) 512-0770
Email: revolutionanalytics@schwartzmsl.com