Example Concept: Anomaly detection in BigQuery typically involves using SQL to calculate statistical measures such as averages and standard deviations over a defined period. By comparing current sales data against these measures, you can identify values that fall outside expected ranges, signaling potential anomalies. This process often includes creating a time series of sales data and applying statistical tests or machine learning models to detect unusual patterns.