It is our pleasure to announce a new Zementis product, the Universal PMML Plug-in for in-database scoring. Available now for the EMC Greenplum Database, a high-performance massively parallel processing (MPP) database, the plug-in leverages the Predictive Model Markup Language (PMML) to execute predictive models directly within EMC Greenplum, for highly optimized in-database scoring.
Developed by the Data Mining Group (DMG), PMML is supported by all major data mining vendors, e.g., IBM SPSS, SAS, Teradata, FICO, STASTICA, Microstrategy, TIBCO and Revolution Analytics as well as open source tools like R, KNIME and RapidMiner. With PMML, models built in any of these data mining tools can now instantly be deployed in the EMC Greenplum database. The net result is the ability to leverage the power of standards-based predictive analytics on a massive scale, right where the data resides.
"By partnering with Zementis, a true PMML innovator, we are able to offer a vendor-agnostic solution for moving enterprise-level predictive analytics into the database execution environment," said Dr. Steven Hillion, Vice President of Analytics at EMC Greenplum. "With Zementis and PMML, the de-facto standard for representing data mining models, we are eliminating the need to recode predictive analytic models in order to deploy them within our database. In turn, this enables an analyst to reduce the time to insight required in most businesses today."
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