Big Data Analysis for R using Revolution R Enterprise
|Presented:||Wednesday, Aug 25th, 2010|
|Presenters:||David Smith, Vice President of Marketing & Joseph Rickert, Pre-sales Engineer, Revolution Analytics|
The R language is well-established as the modern language for predictive analytics. However, given the deluge of data that must be processed and analyzed today, some organizations have been reluctant to deploy R beyond research into production applications. Additionally, R's in-memory design offers great flexibility, but can be limiting when processing multi-gigabyte or terabyte-class datasets.
Revolution R Enterprise now extends the reach of R into the realm of 'Big Data' data analysis. This webinar will introduce R users to Revolution's new RevoScaleR package, which provides unprecedented levels of performance and capacity for statistical analysis of very large data sets in the R environment. We'll demonstrate how Revolution R Enterprise can process, visualize and model this scale of data in a fraction of the time of legacy systems—without the need of expensive or specialized hardware.
In this webinar, David Smith of Revolution Analytics will introduce the capabilities of the high-performance RevoScaleR package:
- The XDF file format, a new binary ‘Big Data’ file format with an interface to the R language that provides high-speed access to arbitrary rows, blocks and columns of data.
- A collection of widely-used statistical algorithms optimized for Big Data, including high-performance implementations of Summary Statistics, Linear Regression, Binomial Logistic Regression and Crosstabs.
- Data Reading & Transformation tools for interactively exploring and preparing large data sets for analysis.
- Extensibility features that allow expert R users to develop and extend their own statistical algorithms.