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PMML-based Predictive Analytics on a Massive Parallel Scale

As you probably know, Apache Hadoop is a Java-based framework that supports the parallel processing of large data sets in a distributed environment, to scale cost-effectively to thousands of servers and petabytes of data. Hadoop was inspired by Google's MapReduce which is a software framework patented by Google to support distributed computing for large data sets.

Now, imagine being able to execute predictive analytics on such a scale? And, guess what? It just became a reality.

Today, Datameer and Zementis announced a strategic partnership to help companies easily deploy, execute and integrate scalable standards-based predictive analytics.

Click here to read press release on KDNuggets!

Datameer is a provider of big data analytics based on Hadoop. Their solution, called DAS (Datameer Analytics Solution), includes data source integration, storage, an analytics engine and visualization. With an ADAPA plug-in for DAS, the Zementis platform for predictive decisioning is now available for companies all around the globe to easily deploy, execute and integrate scalable standards-based predictive analytics on a massive scale.

ADAPA combines predictive analtyics and business rules to provide a true enterprise decision management system. Based on PMML, the Predictive Model Markup Language, ADAPA is able to execute predictive models as well as data pre- and post processing for solutions built in PMML compliant applications.

Conceived by the Data Mining Group (DMG), PMML is the de facto standard to represent predictive solutions. In fact, it is today supported by all the top commercial and open source analytics tools including IBM/SPSS, SAS, Microstrategy, KNIME, Rapid-I, Zementis
ADAPA and several others (click here for a complete list).

Standards-based predictive analytics on a massive parallel scale is here!

Tags: ADAPA, Analytics, DAS, Data, Datameer, Hadoop, Mining, PMML, Predictive, Zementis

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