Question

Can Power BI automatically detect anomalies in historical data or do I need to manually configure it?
I have historical data plotted in a time series visual, and I want Power BI to identify past anomalies without configuring detection for each period. Does Power BI support automatic detection of anomalies in existing data, or must I define parameters manually for each instance?

Answer 1

Yes, Power BI can automatically detect anomalies in historical time series data without the need for manual configuration for each period. Once you add a line chart with a valid date/time field on the X-axis and a numerical measure on the Y-axis, you can right-click the data line and choose "Find anomalies". Power BI will then analyze the entire historical dataset and highlight points that deviate significantly from expected trends.

The anomaly detection feature uses built-in machine learning models to automatically determine baselines and detect unusual spikes or dips across the full time range. You don’t need to manually configure detection for specific time windows or data points. Power BI evaluates historical trends and flags anomalies based on statistical outliers and the underlying distribution of the data.

Additionally, you can fine-tune sensitivity or customize the analysis through the Analytics pane, but these are optional adjustments. The default setup is designed to work out-of-the-box, making it easy to surface past anomalies for time-based metrics with minimal effort. The anomalies also respond to user-applied filters, so they stay relevant in dynamic reporting environments.