What is ModelOps?
Definition: Model operationalization (ModelOps) is primarily focused on the end-to-end governance and life cycle management of all analytics, AI and decision models
MLOps vs. ModelOps
MLOps is for Data Scientists
ModelOps is for the Enterprise
Difference
ModelOps
Feature in data science platforms
MLOps
Enterprise capability
What is it?
ModelOps
Rapid experimentation and deployment of ML models during the data science process
MLOps
Enterprise governance and operations for models in production
Owner
ModelOps
Data Scientist within Line of Business
MLOps
CIO/IT
Primary Users
ModelOps
Data Scientists
MLOps
Enterprise Risk, Enterprise IT or Line of Business Operations
Primary Capabilities
ModelOps
Tight integration with specific data science platform
Rapid deployment of models for experimentation & testing during model development
Data science performance focused monitoring integrated with specific data science platforms
Rapid deployment of models for experimentation & testing during model development
Data science performance focused monitoring integrated with specific data science platforms
MLOps
Enterprise-wide product model inventory
Complete model life cycle automation
360-degree enterprise visibility, monitoring, auditability for all models in production
Complete model life cycle automation
360-degree enterprise visibility, monitoring, auditability for all models in production