Detecting Anomalies With Machine Learning

The strategy there is to take every, every column and every table that you care about and compute a bunch of different metrics. And for each of those metrics, observe it over time and do anomaly detection and time series. We use great of boosted decision trees to look at samples of data from tables. It's able to make this separation that allow me to detect which records are coming from today versus yesterday.