Exploring outliers and key drivers with ML-powered anomaly detection and contribution analysis - Amazon QuickSight

Exploring outliers and key drivers with ML-powered anomaly detection and contribution analysis

You can interactively explore the anomalies (also known as outliers) in your analysis, along with the contributors (key drivers). The analysis is available for you to explore after the ML-powered anomaly detection runs. The changes you make in this screen aren't saved when you go back to the analysis.

To begin, choose Explore anomalies in the insight. The following screenshot shows the anomalies screen as it appears when you first open it. In this example, contributors analysis is set up and shows two key drivers.

Anomalies analysis with contributors shown.

The sections of the screen include the following, from top left to bottom right:

  • Contributors displays key drivers. To see this section, you need to have contributors set up in your anomaly configuration.

  • Controls contains settings for anomaly exploration.

  • Number of anomalies displays outliers detected over time. You can hide or show this chart section.

  • Your field names for category or dimension fields act as titles for charts that show anomalies for each category or dimension.

The following sections provide detailed information for each aspect of exploring anomalies.