Important: We've redesigned the Amazon QuickSight analysis workspace. You might encounter screenshots or procedural text that doesn't reflect the new look in the QuickSight console. We're in the process of updating screenshots and procedural text.
To find a feature or item, use the Quick search bar.
For more information on QuickSight's new look, see Introducing new analysis experience on Amazon QuickSight
Detecting outliers with ML-powered anomaly detection
Amazon QuickSight uses proven Amazon technology to continuously run ML-powered anomaly detection across millions of metrics to discover hidden trends and outliers in your data. This tool allows you to get deep insights that are often buried in the aggregates and not scalable with manual analysis. With ML-powered anomaly detection, you can find outliers in your data without the need for manual analysis, custom development, or ML domain expertise.
Amazon QuickSight notifies you in your visuals if it detects that you can analyze an anomaly or do some forecasting on your data.
Important
ML-powered anomaly detection is a compute-intense task. Before you start using it, you can
get an idea of costs by analyzing the amount of data that you want to use. We offer
a tiered pricing model that is based on the number of metrics you process per month.
To learn more about usage-based pricing, see Amazon QuickSight Pricing
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