Data engineering is the unsung hero of the analytics revolution. While machine learning algorithms get all the spotlight, the quality of data can make or break an analytics project. Missing data or entry errors are just the tip of the iceberg: Thoughtfully creating new variables that are tailor-made for the business problem at hand will pay long-lasting dividends in terms of model accuracy and effectiveness. As Yogi Berra said, “it’s tough to make predictions, especially about the future”. Predictive analytics assumes “business as usual”, which really means “business as before”, and that’s an increasingly questionable assumption today. To successfully predict the future requires developing a deeper understanding of what drives people’s behavior.
Are you working in marketing or customer analytics? Measuring and increasing lifetime value, reducing churn, and optimizing marketing communication requires going beyond correlations to identify the true causes of behavior. So come get your behavioral edge by attending the “The Behavioral Edge: level up your data skills with behavioral science” by Florent Buisson
