SAS and Microsoft integrate SAS Model Manager with Azure Machine Learning to streamline ModelOps—managing the full machine learning lifecycle from creation to deployment, monitoring, and retraining. SAS Model Manager offers centralized governance, version control, and no-code/low-code tools, while Azure ML enables scalable, secure deployments across the Microsoft Cloud and edge. Best practices include creating repeatable ML pipelines, automating rollout and audit trails, monitoring performance and drift, and accelerating retraining. This approach improves collaboration, reduces risk, and ensures models remain accurate and business-relevant at scale.

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