Metrics

Where in traditional data quality tools, a "rule" is the most common unit of measurement, in data observability the most common unit is a "metric". It is a statistic that is calculated over the data which can then be tracked as a time series.

Examples:

• The average value of the price_per_unit column in the orders table.
• The percent of rows with a null user_uuid column.

Bigeye monitors metrics for database tables or columns and alert you if they go out of bounds.

To get started with metrics, navigate from the Catalog navigation pane to the source, schema, table, or column you are interested in.