SAS
About SAS
SAS Model Manager enhances the model management experience by allowing data scientists and MLOps engineers to streamline processes from creation to deployment. The platform's unique features include governance, tracking, and monitoring, ensuring rapid and responsible model management for organizations focused on analytic efficiency.
SAS Model Manager offers flexible pricing plans, catering to businesses of all sizes. Users can choose from various subscription tiers, each designed to provide specific features and benefits. Upgrading not only enhances model management capabilities but also delivers greater value through advanced analytics toolsets.
SAS Model Manager features an intuitive user interface designed for seamless navigation. Its layout promotes easy access to key functionalities, while features like no-code model validation ensure users can effectively manage their analytics projects, creating an efficient and user-friendly experience.
How SAS works
Users interact with SAS Model Manager by first onboarding, where they create accounts and set preferences. They can then easily navigate the main features like model creation, validation, and deployment. The platform's no-code interface simplifies model testing, while built-in monitoring tools help track performance, making the entire process efficient and user-friendly.
Key Features for SAS
Model Lifecycle Management
SAS Model Manager uniquely facilitates comprehensive model lifecycle management, allowing users to efficiently oversee model creation, validation, deployment, and monitoring. This innovative feature ensures that data scientists and MLOps engineers can collaborate effectively while maintaining oversight over critical analytics processes within the platform.
Automated CI/CD Pipeline
SAS Model Manager's automated Continuous Integration and Continuous Delivery (CI/CD) pipeline enhances efficiency by minimizing manual efforts in model deployment. This feature allows organizations to standardize their modeling assets, ensuring smooth automation while keeping teams informed on model performance and alerts in real-time.
Model Monitoring
SAS Model Manager includes robust monitoring capabilities that illuminate data, concept, and model drift through continuous oversight. This feature allows stakeholders to receive alerts on model decay, helping organizations maintain optimal performance and mitigate downtime effectively, which is crucial for responsive analytics strategy.
