Thursday, February 28, 2013

In-database scoring with Teradata and Teradata Aster

The partnership between Zementis and Teradata allows customers with a variety of data mining tools to efficiently deploy predictive models based on the Predictive Model Markup Language (PMML) standard.  Focused on Big Data applications, the Universal PMML Plug-in (UPPI) for Teradata enables scalable execution of standards-based predictive analytics directly within the Teradata data warehouse.

To read more about the benefits of running your predictive solutions inside Teradata and Teradata Aster, please visit:

PMML Scoring

Zementis offers a range of products that make possible the deployment of predictive solutions and data mining models built in all the top commercial and open-source data mining vendors. Our products include the ADAPA Scoring Engine for real-time scoring and UPPI, which is currently available for a host of database platforms as well as Hadoop/Datameer. For a list of available platforms, please visit our in-database products page.


Not all analytic tasks are born the same. If one is confronted with massive volumes of data that need to be scored on a regular basis, in-database scoring sounds like the logical thing to do. In all likelihood, the data in this case is already stored in a database and, with in-database scoring, there is no data movement. Data and models reside together hence scores and predictions flow on an accelerated pace

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