Feature Stores are Critical for Scaling ML Initiatives and Accelerating both Top-line and Bottom-line Impact

Feature stores are emerging as a critical component of the infrastructure stack for ML. They solve the hardest part of operationalizing ML: building and serving ML data to production. They allow data scientists to build more accurate ML features and deploy these features to production within hours instead of months.