Last updated: July 22, 2025
DQOps YAML file definitions
The definition of YAML files used by DQOps to configure the data sources, monitored tables, and the configuration of activated data quality checks.
TableLevelDataQualityPolicyYaml
The configuration of a data quality policy at a table level, containing data quality checks that are applied on tables that match a search pattern.
The structure of this object is described below
| Property name | Description | Data type | Enum values | Default value | Sample values |
|---|---|---|---|---|---|
api_version |
DQOps YAML schema version | string | dqo/v1 | ||
kind |
File type | enum | source table sensor provider_sensor rule check settings file_index connection_similarity_index dashboards default_schedules default_checks default_table_checks default_column_checks default_notifications |
default_table_checks | |
spec |
The specification (configuration) of the table-level data quality policy with checks that are applied on tables matching a pattern | TableQualityPolicySpec |
TableQualityPolicySpec
The default configuration of table-level data quality checks that are enabled as data observability checks to analyze basic measures and detect anomalies on tables. This configuration serves as a data quality policy that defines the data quality checks that are verified on matching tables.
The structure of this object is described below
| Property name | Description | Data type | Enum values | Default value | Sample values |
|---|---|---|---|---|---|
priority |
The priority of the pattern. Patterns with lower values are applied before patterns with higher priority values. | integer | |||
disabled |
Disables this data quality check configuration. The checks will not be activated. | boolean | |||
description |
The description (documentation) of this data quality check configuration. | string | |||
target |
The target table filter that are filtering the table and connection on which the default checks are applied. | TargetTablePatternSpec | |||
profiling_checks |
Configuration of data quality profiling checks that are enabled. Pick a check from a category, apply the parameters and rules to enable it. | TableProfilingCheckCategoriesSpec | |||
monitoring_checks |
Configuration of table level monitoring checks. Monitoring checks are data quality checks that are evaluated for each period of time (daily, weekly, monthly, etc.). A monitoring check stores only the most recent data quality check result for each period of time. | TableMonitoringCheckCategoriesSpec | |||
partitioned_checks |
Configuration of table level date/time partitioned checks. Partitioned data quality checks are evaluated for each partition separately, raising separate alerts at a partition level. The table does not need to be physically partitioned by date, it is possible to run data quality checks for each day or month of data separately. | TablePartitionedCheckCategoriesSpec |
TargetTablePatternSpec
The configuration of a table pattern to match default table checks.
The structure of this object is described below
| Property name | Description | Data type | Enum values | Default value | Sample values |
|---|---|---|---|---|---|
connection |
The data source connection name filter. Accepts wildcards in the format: conn, , conn*. | string | |||
schema |
The schema name filter. Accepts wildcards in the format: _prod, , pub*. | string | |||
table |
The table name filter. Accepts wildcards in the format: _customers, , fact_*. | string | |||
stage |
The table stage filter. Accepts wildcards in the format: _landing, , staging_*. | string | |||
table_priority |
The maximum table priority (inclusive) for tables that are covered by the default checks. | integer | |||
label |
The label filter. Accepts wildcards in the format: _customers, , fact_*. The label must be present on the connection or table. | string |