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SAS Model Manager

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What is SAS Model Manager?

SAS Model Manager helps operationalize analytics by streamlining the model management lifecycle from creation to deployment. It has seamless integration capabilities with the SAS Viya platform and supports a wide range of uses, from fraud detection to customer experience optimization. With its robust suite of tools and features, SAS Model Manager enables efficient scoring, monitoring, and retraining of models across various deployment environments, thus ensuring consistency and compliance.

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SAS Model Manager's Top Features

Key capabilities that make SAS Model Manager stand out.

Model scoring

Monitoring and retraining

Seamless integration with SAS Viya

Support for AI and machine learning models

Compliance and governance

Flexible deployment options

Robust analytics workflow management

Industry-specific analytics support

Real-time model performance tracking

Comprehensive user resources

Key Details

Pricing Model
Free
Last Updated
August 8, 2024

Tags

SAS Model Manageranalyticsmodel managementdeploymentSAS Viyafraud detectioncustomer experience optimizationscoringmonitoringretrainingcompliance

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Use Cases

Who benefits most from this tool.

Data Scientists

Operationalize and streamline the lifecycle of machine learning models from creation to deployment.

Risk Analysts

Manage and monitor risk assessment models to ensure accuracy and compliance.

Marketing Teams

Optimize customer experience by deploying and managing predictive models effectively.

Fraud Detection Specialists

Deploy and monitor fraud detection models in real-time to mitigate risks.

IT Professionals

Ensure seamless integration and deployment of analytics models across different environments.

Compliance Officers

Leverage model management tools to maintain compliance and governance.

Retail Analysts

Analyze consumer behavior and optimize inventory through predictive modeling.

Healthcare Analysts

Drive healthcare improvements by managing models aimed at predicting patient outcomes.

Insurance Analysts

Enhance risk management efforts by deploying accurate and compliant models.

Public Sector Analysts

Utilize model management for public sector applications such as resource allocation and policy evaluation.

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