Time series forecasting is a powerful way to use current or historical data to monitor, clarify, and predict “cause and effect” behaviors which can better inform future decisions. Anomaly detection for a time series can detect critical incidents such as fraudulent behaviors or potential opportunities such as changes in consumer buying patterns. Join this talk, to see the newest features in BigQuery ML in action and simplify your workflow in time forecasting and anomaly detection.