Built-in Metrics¶

These metrics are calculated in Data Observability out-of-box.

Metric	Description
Total Record Count	The total size of the monitored table. This is only available when CDC is enabled (i.e., the “delta only” flag is on). If the flag is off or the monitored source is not an SQL database, this field will be set to N/A.
Record Count	If CDC is enabled it reflects the size of the delta, otherwise, it's the size of the entire set of data.
Completeness	Percentage of not null/missing/placeholder values. Completeness is tracked both at the data source level as well as the attribute level: Attribute level: percent of records where the attribute value is not null, not empty, or not one of the user-defined placeholders like N/A. Data Source level: the compounded average of all attribute level completeness within a data source.
Freshness	Table-level freshness is based on the time since the table was last updated. It is available for Snowflake, BigQuery, Databricks/Delta Lake, and Hive/Iceberg (derived from table metadata), and for Firebolt, Redshift, and Oracle (requires a timestamp attribute). It is not computed for generic JDBC sources (e.g., Trino, MySQL, Microsoft SQL Server, Athena) or for cloud storage assets (S3, GCS, Azure Blob, OneLake).
Uniqueness	Uniqueness of the records based on an ID attribute. The KPI measures the ratio of records with unique id versus the total number of records. For example, if out of 10 records, there are 2 records sharing the same value the uniqueness is 80%. An attribute can be marked as an ID attribute in the Advanced section of the Edit Connection menu. If ID attribute is not configured this KPI will be N/A
Contains PII	Value contains PII pattern for either of: Credit cards IP Addresses Social security numbers Phone numbers Zip codes Email Credit card
Length	String length