1. A computer-implemented system for detecting anomalies using sample-based rule identification, comprising: data for data analytics in a database; a set of anomaly rules; a statistical anomaly detector configured to statistically identify a rare pattern in the data; a label module configured to label the identified rare pattern as at least one of anomaly and non-anomaly based on verification by a domain expert; a sample-based rule identifier configured to adjust the set of anomaly rules based on the labeled anomaly; a detecting and classifying other anomalies in the data by applying the adjusted set of anomaly rules to the data; and a processor to execute the modules.