Question

How can I customize the sensitivity of anomaly detection in Power BI?
I want to fine-tune the anomaly detection feature in Power BI to make it more or less sensitive to fluctuations in my data. Specifically, I need to understand how to adjust sensitivity settings to control the number of anomalies detected. What is the best approach to achieve this, and where can I configure these options for optimal results?

Answer 1

In Power BI, you can customize the sensitivity of anomaly detection directly within the analytics pane when using a line chart visual. The "Find anomalies" feature allows you to detect unexpected changes in time series data, and the sensitivity setting lets you control how responsive the model is to variations. A higher sensitivity detects smaller changes (more anomalies), while a lower sensitivity only flags larger, more significant deviations.

To adjust sensitivity, click on your line chart, open the Analytics pane, and select "Find anomalies". You’ll see a Sensitivity slider, which ranges from 0 to 100. Moving the slider to the right increases sensitivity, meaning the algorithm becomes more aggressive in flagging outliers. Adjust this setting based on the nature of your data and how many anomalies you expect to see.

For best results, test the sensitivity setting across different datasets or time periods to find a balanced threshold that suits your business use case. It’s also helpful to use the Explain anomalies option, which provides insights into what may be driving the anomalies, helping you validate whether the flagged points are meaningful or just noise.