Predictors can be used to dramatically improve the effectiveness of business decisions. For most companies, deploying predictive models into productive systems is a significant IT project involving reprogramming data feeds, creating variables and hand-coding model algorithms in a language such as C++ or COBOL. The process is time-consuming and makes it difficult to incorporate new models as business needs change.

This white paper discusses methods for effectively managing the entire modeling lifecycle. Discover a structured yet flexible environment for quickly assembling model development steps using intuitive data management and analytic components. Explore how sharing a common repository and platform with IT makes deployment of analytics seamless by eliminating the need to reprogram logic in operational business processes. Learn how to effectively organize model development and quickly and efficiently deploy analytics for optimized business decision capabilities.