Standards-based Deployment of Predictive Analytics
Using a standards-based approach to deploy predictive analytics on operational systems from mainframes to Hadoop.
Predictive analytics is a powerful tool for managing risk, reducing fraud and maximizing customer value. Organizations succeeding with predictive analytics are looking for ways to scale and speed up their programs and make predictive analytics pervasive. 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.
Once you are able to rapidly deploy the models built by your data science team, you will be able to take advantage of smarter decisions. With open standards, it is easy to inject predictive models into batch scoring solutions in Hadoop or in-database. Even better, execute predictive models at the point of greatest impact, in your real-time transaction system and on streaming data.
To learn how to efficiently deploy advanced machine learning and predictive models, we invite you to download our latest white paper, authored by renowned industry analyst and decision management expert James Taylor.
Download white paper: Standards-based deployment of predictive analytics
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