Tech

Advanced Analytics | Data Management | Machine Learning
Thomas Wileman 0
Registering the whole pipeline, not just the model

Most machine learning models produce a probability, but many times logic is applied to that prediction to produce a decision. That last logic step often lives in a downstream script disconnected from the model it depends on, easy to lose when the model is refreshed. Using the home equity (HMEQ) dataset, this post walks through a practical alternative in SAS Model Studio. A SAS Code node placed after the modeling node weights the predicted default probability by the requested loan amount to produce expected loss in dollars, and the new Model Registration node (2026.05) accumulates that logic into a single model registered in SAS Model Manager. The result is a model and its decision logic captured as one governed, versioned artifact, so whoever scores the model gets the decision-ready output computed the same way every time.

Advanced Analytics | Data Visualization | Innovation
Sasha Karpinski 1
From question to clarity: how SAS Viya Copilot changes the way we work with data

Most analytical journeys start the same way – with a question. When did we have the highest profit? Which customers are driving growth? What segment should we look at next? In traditional analytic workflows, turning those questions into answers often requires navigating menus, configuring visuals, writing calculations and interpreting results

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