Align data definitions before deploying the model.

The biggest pitfall I've encountered in data and model projects isn't that the algorithms aren't advanced enough, but that the training data, online data, and reporting data all use different definitions. The AUC looks great offline, but once deployed, you find that the online features are missing a cleaning logic, causing the scores to drift immediately. Later, I got into the habit of focusing…