Predictive Analytics Deployment to Mainframe or Hadoop

Learn how to achieve a standards-based, efficient approach to analytics deployment from open source like R and commercial analytics products to a wide range of platforms including mainframes like IBM zSystems and new data infrastructure like Hadoop.

The big challenge for analytics-driven organizations today is closing the gap between deriving an analytic result and getting the ROI. Organizations need a consistent and efficient way to deploy analytic results into everything from systems of record like mainframes to modern big data infrastructure.

Join James Taylor, CEO of Decision Management Solutions and Michael Zeller, CEO of Zementis, in this live webinar recording to learn how the Predictive Model Markup Language (PMML) provides an XML standard that streamlines the deployment of predictive analytic models. With PMML a model can be developed in one tool or language, whether open source like R or commercial predictive analytics products, and easily migrated to a wide range of operational systems including mainframes like IBM zSystems and new data infrastructure like Hadoop with Spark / Storm / Hive.




Webinar Link