Streamlined analytical model deployment
Provides a common method for accessing and managing information, selecting analytical models, and defining business rules that create context for production use.
Deliver relevant, interactive decisions based on automated, sophisticated analytics. IT and business users can use current and historical operational data – informed by analytical models and governed by business rules – to jointly engineer and deploy operational decisions that automatically define real-time best actions at scale across thousands of daily decisions. From direct, customer-facing decisions (e.g., offer targeting and credit decisioning) to complex, cross-functional decisions in areas like manufacturing, you can be confident that enterprise decisions are efficient, effective and timely.
A common decision authoring and deployment environment dramatically reduces the time required for IT to validate and deploy analytical models – whether written in SAS, open source or custom code. From a single interface, you can natively integrate, manage and deploy SAS and Python analytical models, custom code and business rules, with identical logic for both batch and real-time web service execution. That means faster deployment and confidence in the integrity of your analytically driven operational decisions.
It doesn't matter how high your data and decision volumes go; you'll always be able to make the best operational and customer decisions exactly when you need to. No need to worry about sluggish, nonresponsive computing resources that will delay decisions when volumes are high. Built on a multitier architecture with server clustering capabilities, our solution delivers scalability and enterprise data throughput for timely, accurate decisions – even in high-volume, 24/7 businesses.
Not a technical guru? No need to be. An intuitive, user-friendly interface lets you easily construct and modify automated decisioning processes – and even incorporate SAS analytical models – without IT assistance. Instead of using cryptic programming and rules, you can design processes by dragging and dropping a set of reusable, out-of-the-box tasks. Shared, flexible processing control logic enables you to select data and models from existing repositories. And defining business rules in context ensures continuity and shared terminology across business functions.
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