Recall that Bigeye's data observability platform works by monitoring metrics for database columns, and alerting you if they go out of bounds. These bounds are called thresholds.

When you deploy an autometric that Bigeye recommended, it comes with autothresholds computed from historical data using machine learning models. You can read more about how you can give feedback to the machine learning models on the Issues page. Autothresholds require a minimum of 5 days of data to produce thresholds. Tables with Row Creation Time enabled can backfill most metrics in order to immediately produce thresholds.


Autothreshold sensitivity can be adjusted after metric creation in case the metric is alerting too often or isn’t alerting often enough. If the threshold is set to wide or extra wide, it will increase the bounds and produce fewer alerts; thresholds set too narrow will decrease the bounds and alert more frequently.

To adjust autothreshold sensitivity, select the relevant metrics under Catalog. Then select Edit from the the Action dropdown menu.


In some cases, you may only want to track and upper or lower bounds for a metric. For example, freshness metrics are upper bound only by default - meaning they will only alert if the data is late, but not if it is delivered earlier than usual. Similarly, for some columns you may not care if the percent of NULL values drops but you do want to be notified if it increases. You can adjust autothreshold bound settings to upper and lower, upper only or lower only when editing a metric.