Mu Sigma Helps Companies Accelerate Big Data Analysis With First Packaged MapReduce Algorithms for Hadoop

Mu Sigma Helps Companies Accelerate Big Data Analysis With First Packaged MapReduce Algorithms for Hadoop. New Offering from Mu Sigma helps accelerate Big Data Analysis Projects; in Testing, Mu Sigma's Offering Consistently Outperformed Commercial Software Tools. End Quote

(1888PressRelease) August 02, 2013 - CHICAGO, IL - Mu Sigma (http://www.mu-sigma.com), the largest pure-play provider of decision sciences and analytics solutions for global enterprise customers, launched a new addition to its series of analytical products. muHPC™ (for High Performance Computing) is a library of popular statistical algorithms written in MapReduce, designed for enterprise-class Big Data analysis in Hadoop environments. As with Mu Sigma's other products, muHPC was successfully and extensively used within Mu Sigma on many client engagements before the company brought it to market.

Traditionally, enterprises that wanted to leverage R and Hadoop for Big Data analysis have had to write their own algorithms, or rely on open-source options that had not been widely used or tested. Quality varied, and it was a challenge for companies to acquire talent with relevant skills and competencies in order to code their own algorithms. Mu Sigma's offering enables enterprises to accelerate their R and Hadoop initiatives, and their overall Big Data analysis programs. In testing, muHPC packages consistently outperformed a leading commercial software in equivalent procedures in terms of execution time on large data sets -- in fact, muHPC algorithms proved to be 2-4 times faster while achieving the same results.

"We talk with so many large enterprises that want to leverage open-source tools such as R and Hadoop but simply cannot find staff with the requisite skills," said Zubin Dowlaty, Head of Innovation and Development at Mu Sigma -- the group responsible for developing new technology solutions for Mu Sigma's internal use and for eventual launch to the public. "muHPC directly addresses that market need by providing a packaged set of the most common R-based algorithms that can be used in a Hadoop environment right out of the box. muHPC is a breakthrough concept that removes significant barriers to Big Data analysis."

muHPC consists of three packages currently:

muGLM: Offers easy-to-use R functions for building a wide variety of generalized linear models (OLS, Logistic, Poisson, Negative Binomial, Gamma etc.) on Big Data
muEDA: Offers easy-to-use R functions for performing exploratory analysis on Big Data
muKMeans: Offers easy-to-use R functions for data clustering on Big Data using the K-means algorithm
Mu Sigma leveraged technology from Cloudera and Revolution Analytics to build muHPC. "Cloudera's Distribution including Apache Hadoop is a great platform for organizations to store and analyze data," said Tim Stevens, vice president, Business Development, Cloudera. "Mu Sigma developing and certifying their new solution on top of Cloudera ensures that their approach to solving big data challenges is both innovative and effective."

muHPC algorithms have been written using components from Revolution Analytics' open-source RHadoop project. Hadoop integration is based on the rmr2 package, which provides Hadoop MapReduce functionality in R, and has been implemented and tested with Cloudera's distribution of Hadoop and Revolution R Enterprise. "Mu Sigma's initiative to utilize open-source R packages for commercial implementations provides a great impetus to R's popularity and it being adopted as the standard environment for mainstream analytical analysis," said Greg Fuller, Vice President, Partners and Channels at Revolution Analytics. "We are very pleased that our Alliance partners are building differentiated solutions based on Revolution Analytics solutions. We look forward to doing even more with our partners as we further develop Revolution R Enterprise Platform-as-a-Service."

muHPC is available now, and comes with an annual subscription license on a per-cluster basis with an incremental price per-node. To learn more, visit www.mu-sigma.com/muhpc.

###

space

Other Related Press Releases