SAS

About SAS

SAS Model Manager is designed for analytics professionals, enhancing the modeling lifecycle from creation to deployment. Its key feature is a no-code interface for model validation, simplifying the process of governance and monitoring. This seamless integration helps users manage models efficiently while ensuring accuracy and transparency.

SAS Model Manager offers various pricing options tailored to user needs. Each tier includes features like model governance and automated CI/CD pipelines, providing great value. Higher tiers grant access to advanced analytics tools and additional monitoring capabilities, ensuring users maximize their investment in model management.

SAS Model Manager boasts a user-friendly interface that simplifies model management tasks. The layout allows for intuitive navigation through model tracking and deployment features. Its design emphasizes clarity and ease of use, making it accessible for data scientists and stakeholders alike in efficiently managing their modeling processes.

How SAS works

Users start with SAS Model Manager by creating an account and completing a quick onboarding tutorial. Once onboarded, they can easily track and manage model assets using the organized interface. The platform integrates no-code validation and deployment tools, quickly transitioning from model creation to deployment while monitoring ongoing performance metrics.

Key Features for SAS

No-Code Model Validation

The no-code model validation feature of SAS Model Manager allows users to effortlessly test and validate their models without needing extensive coding skills. This user-friendly function simplifies the process of ensuring models perform correctly, enhancing its appeal to users at all experience levels.

Automated CI/CD Pipeline

SAS Model Manager's automated Continuous Integration and Continuous Delivery (CI/CD) pipeline simplifies model deployment. This feature streamlines the workflow for MLOps teams, maximizing efficiency and reducing manual effort, ensuring that models can be deployed quickly and accurately across various environments.

Model Drift Monitoring

SAS Model Manager includes advanced capabilities for monitoring model drift, alerting users to changes that may affect performance. This proactive feature ensures that data scientists can address issues swiftly to maintain model accuracy and reliability, ultimately providing a competitive edge in analytics.