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. But while organizations across industries are adept at collecting and analyzing massive data troves, many struggle to operationalize analytics to capture the full value of data-driven decision making. Learn how “ModelOps,” an emerging analytics methodology, can help organizations operationalize the full analytics life cycle at scale.