Teradata and other partners have previously supported Revolution's software, but Teradata says it's the first to bring efficient, parallel processing to the vendor's High-Performance R offering. "We used to run the software at the node level, where you were reliant on the data scientist to determine parallelism," Teradata product and services marketing manager Chris Twogood told InformationWeek in a phone interview. "Now we're driving results in parallel, whether you're doing data manipulation, descriptive statistics or predictive algorithms." [ Want the scoop on the latest big analytics move? Read SAP Buying KXEN For Predictive Analytics. ] The bottom line of automated, parallelized processing is faster performance and greater accuracy.