SAS
About SAS
SAS Model Manager empowers data scientists and MLOps engineers to streamline the entire analytical modeling lifecycle. By offering a user-friendly, no-code interface, it enables rapid creation, validation, and deployment of models. This innovative platform enhances collaboration, governance, and monitoring, allowing teams to optimize their modeling processes effectively.
SAS Model Manager features flexible pricing plans catering to diverse needs. Subscriptions include essential model management features, with premium tiers offering advanced monitoring and customization options. Users benefit from streamlined model lifecycle processes, and special discounts may apply, providing excellent value for teams looking to enhance their analytics capabilities.
SAS Model Manager's intuitive user interface ensures a seamless experience for users. Its clean layout and organized navigation allow quick access to tools and features. Enhanced with user-friendly functionalities, SAS Model Manager offers an efficient means to manage models, ensuring that users can focus on better analytics and insights.
How SAS works
Upon onboarding, users of SAS Model Manager can easily navigate the platform to create, validate, and deploy analytical models. The streamlined process includes a no-code interface for testing and monitoring models, facilitating collaboration among data scientists and MLOps engineers. Continuous integration and automated monitoring help ensure optimal performance and compliance.
Key Features for SAS
Automated CI/CD Pipeline
SAS Model Manager’s automated Continuous Integration and Continuous Delivery (CI/CD) pipeline optimizes deployment efficiency. This feature allows teams to streamline processes by automating model delivery and monitoring, ultimately reducing manual efforts and ensuring high-quality, rapid deployment across various environments to meet dynamic business needs.
Model Validation Tools
SAS Model Manager includes robust model validation tools that ensure reliable performance in production environments. Users can easily test and validate their model scoring logic through a no-code interface, streamlining the validation process, enhancing model quality, and supporting compliance with data governance standards.
Monitoring and Alerts
With built-in monitoring and alert systems, SAS Model Manager effectively detects data, concept, and model drift. This feature not only enhances operational transparency but also enables stakeholders to identify model decay promptly, minimizing potential downtime and ensuring that AI models remain accurate and effective over time.
