ModelOps: Maximizing Value Across the Analytics Life Cycle

The global health crisis has underscored the importance of analytics models for predicting hot spots, identifying medical needs and determining priorities. Clearly, data and modeling have been used to answer lots of questions and will play an even bigger role as businesses begin to resume their efforts and effectively mitigate disruptions caused by COVID-19. It’s an opportunity to reconsider how you’re operating and applying lessons learned during this outbreak and how you can be more agile and responsive in the future.

Companies invest a great deal of time and money in developing analytics. But deployment is always a challenge and lengthy delays mean wasted development efforts that never deliver their expected value. Learn how "ModelOps," an emerging analytics methodology, can help your organization move quality analytic models through development, validation, deployment and monitoring as quickly as possible to drive valuable business decisions.

 Digital
SAS

Share content on email

Share