What is it

SAS Model Manager centralizes and streamlines the analytical modeling lifecycle, from model creation to deployment, management, and monitoring. It includes a searchable model repository, custom workflow automation, and REST API access for programmatic interaction.

Key Features

SAS Model Manager offers the following key features:

• Centralized & searchable model repository
• Task automation with custom workflows
• Build once, deploy everywhere
• Programming-only interaction through REST APIs
• Cloud native architecture

Pros

Enhanced Collaboration: Connects data scientists, MLOPs engineers, and business analysts, enabling quick model deployment and integration with open source.

Model Validation and Quality Assurance: Validates models to ensure high-quality predictions.

Automated Performance Monitoring: Automatically monitors the performance of models, generating alerts to indicate model decay.

Continuous Model Updates: Allows continuous updating of models to keep pace with changing market and business conditions.

Cons

Cost: SAS Model Manager can be a costly investment, especially for smaller organizations.

Learning curve: The software can have a steep learning curve, requiring significant training and onboarding for users.

Summary

SAS Model Manager is a comprehensive software solution for managing and deploying analytical models. It offers a centralized repository, automated workflows, and REST API access, enabling efficient collaboration, model validation, performance monitoring, and continuous updates. While it can be a costly investment with a learning curve, SAS Model Manager provides significant benefits for organizations seeking to streamline their analytical modeling lifecycle.