Wednesday, October 17, 2012

Lavastorm Analytics Joins the Power of R Programming with its Visual Analytic Modeling Products


New R Analytics Pack Allows Business Analysts and R Programmers to Rapidly Combine Statistical and Predictive Analytic Models with Broader Business Intelligence Programs



BOSTON — Lavastorm Analytics, a leading global analytics software company, announced today that the award-winning Lavastorm Analytics Platform and its core Lavastorm Analytics Engine can now directly support statistical and predictive data analytics models written using the open source R programming language. The support comes via the new R Analytics Pack in the Lavastorm Analytics Library that allows enterprises to directly integrate analytics written in R into broader business intelligence (BI) and business data analytics applications using Lavastorm’s drag-and-drop visual discovery interface.

As enterprises increasingly add functions like linear regressions, clustering, and financial modeling to their ongoing analytics programs to become more agile, data-driven businesses, the use of R language-based analytics is rapidly rising. The new R Analytics Pack brings the full capabilities of the Lavastorm Analytics Engine to R programmers, including the ability for them to bring together disparate data, and profile, inspect, and cleanse the data themselves. In addition, the R Analytics Pack extends the Lavastorm Analytics Engine’s core functionality and enables business analysts to perform more statistical, financial, and predictive analyses in tandem with traditional business process analytics to optimize key functions like competitive pricing and customer churn avoidance.

“R-based statistical analyses have emerged as a highly popular language for analyzing cross-functional business processes and a critical tool for complex, Big Data analytics,” said Carl Lehmann, Research Manager, Enterprise Architecture, Integration and Business Process Management at 451 Research. “The trend now is to make investments in R-based analytics more accessible to business analysts, not just the programmers that created them, so that the analytics can be more broadly used across the business to analyze and control various operations, and Lavastorm’s unique visual interface will help this greatly.”

In addition to broadening enterprises’ BI abilities, using the R Pack within the Lavastorm Analytics Engine allows users to quickly and easily turn complex R-based programming code into reusable analytic building-blocks. Lavastorm users can store their R analytics in pre-configured, drag-and-drop functions that can then be deployed with a single click of the mouse to perform customized and persistent analysis of specific business processes.

“R’s emergence has been a natural extension of the explosive rise in use of analytics to optimize business performance,” said Drew Rockwell, CEO, Lavastorm Analytics. “It provides extremely powerful computation functionality, and is designed to be extensible through community-driven libraries like our own Lavastorm Analytics Library. But the ability to connect R’s benefits to broader BI practices has left something to be desired. Our new R Analytics Pack not only extends the Lavastorm platform to encompass completely new types of analyses through R, but also makes R’s unique abilities truly accessible to business analysts. This will be invaluable for enterprises grappling with Big Data challenges.”

The release of the R Analytics Pack follows Lavastorm’s launch of the Enhanced Analytics Pack earlier this year, and furthers the company’s modular approach to introducing new analytic and data integration functions to the Lavastorm Analytics Library. The new R Analytics Pack, replete with training video, is available immediately for use via the Lavastorm Analytics Engine, which has proven capable of performing analytics of complex business data and processes up to 90 percent faster than SQL-based tools.

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