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Deploying Predictive Models: How to Get Real Business Value from Data Science

June 10, 2020

Prerequisite: None

Zank Bennett


Bennett Data Science

Your team has built an analytics model, but your work is not finished. Your next steps will spell the difference between failure and success. To realize the value of analytics, you must deliver data science models in ways useful to stakeholders and customers. Deployment is one of the final steps to take to fully leverage data and realize measurable ROI.

Why is this crucial step such a struggle and so hard to get right?

Industry expert Zank Bennett will present a framework to establish deployment as the final pillar of a complete analytics process. He will reveal proven methods for deployment, from ideation to optimization, with the objective of helping you understand what is required to effectively use AI in production.

Learn why deployment should be one of the earliest conversations you have when starting an AI project, how to work with stakeholders as end users, and how to ensure buy-in. Bennett will highlight the importance of choosing the right metrics to track deployment success, the difference between pre-deployment and post-deployment metrics, and what comes after deployment.

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