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What are QuickSight ML Insights, and how do they help business users find patterns in their data?

Intermediate

Answer

QuickSight ML Insights uses built in machine learning to automatically detect anomalies in your data, such as an unexpected spike or drop in a metric, and generate natural language narratives that summarize key trends and forecasts, giving business users without any data science background the ability to uncover meaningful patterns without writing a single line of analytical code.
// Enabling anomaly detection on a QuickSight visual through the console
// automatically flags unusual data points in a time series chart
Real-world example A finance team uses QuickSight's anomaly detection feature to automatically flag an unexpected spike in refund requests one week, allowing them to investigate the root cause immediately rather than discovering the issue much later during a manual review.

Common follow-ups: How accurate is QuickSight's built in anomaly detection compared to a custom machine learning model?;What data volume is needed for ML Insights to work effectively?