Executive Summary (This is a document excerpt)

In the coming year, a thirst for customer knowledge, a need to generate incremental revenue through understanding buying behavior, the requirement to reduce costs in supply chain logistics, and the imperative to make inferences about the future behavior of these groups will drive predictive analytics. Resulting trends include intensified competition between predictive algorithms wrappered in applications and general-purpose, predictive modeling workbenches; the assimilation of predictive marketing by predictive analytics at large; the emergence of the exploratory data warehouse dedicated to predictive analytics; and the availability of innovative desktop, in-database, and served-based architectural options to address client requirements.

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