Zementis Announces In-Database Scoring Solution for the EMC Greenplum Database

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Universal PMML Plug-in to deliver massively parallel execution of predictive analytics based on open standards

The Universal PMML Plug-in allows the EMC Greenplum Database to leverage the Predictive Model Markup Language (PMML) for highly optimized in-database scoring.

Zementis, a leader in predictive analytics solutions and EMC Corporation (NYSE: EMC), the world leader in information infrastructure solutions, today introduced the Universal PMML Plug-in™ for the EMC Greenplum Database.

The Universal PMML Plug-in enables the execution of standards-based predictive analytics directly within the EMC Greenplum Database, a high-performance massively parallel processing (MPP) database product. The Universal PMML Plug-in allows the EMC Greenplum Database to leverage the Predictive Model Markup Language (PMML) 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, Microstrategy, Tibco and Revolution Analytics as well as open source tools like R, KNIME, Rapid Miner and Weka.

"The PMML standard delivers the promise of true interoperability, offering a mature standard for moving predictive models seamlessly between platforms" said Dr. Michael Zeller, CEO of Zementis. "Models built in most commercial or open source data mining tools can now instantly be deployed in the 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."

In addition to its flagship product, the ADAPA® Decision Engine and cloud computing platform, the Universal PMML Plug-in extends the Zementis product line towards in-database scoring solutions.

"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."

The Universal PMML Plug-in for the EMC Greenplum Database is available now. To learn more about how the EMC Greenplum Database and the Universal PMML Plug-in work together, visit the product page and download the white paper.

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About EMC Greenplum Database
The EMC Greenplum Database utilizes a shared-nothing massively parallel processing (MPP) architecture designed from the ground up for business intelligence and analytical processing on commodity hardware. Data is automatically partitioned across multiple segment servers, and each segment owns and manages a distinct portion of the overall data. This 'shared-nothing' architecture means that all communication is done through a network interconnect and there are no disk-level sharing or contention issues to address. More information about the Greenplum Database is available at http://www.greenplum.com/products/greenplum-database.

About Zementis
Zementis, Inc. is a leading software company focused on the operational deployment and integration of predictive analytics and data mining solutions. Its ADAPA® decision engine successfully bridges the gap between science and engineering. ADAPA® and the Universal PMML Plug-in™ are designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive analytics in any industry. For more information, please visit http://www.zementis.com.


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