In this webinar, we’ll walk through an end-to-end lifecycle of embedding predictive analytics inside an application. Find out how a real-world application decided what predictive questions to ask, sourced the right data, organized resources, built models, deployed predictive analytics in production, and monitored model performance over time.
The most common use cases for predictive analytics, such as increasing sales and reducing customer churn
Top 3 challenges you’ll encounter when creating your predictive model
How to source data from multiple systems and overcome common data challenges