Advanced profiling is a type of check that should be used to profile data and run experiments to see which types of recurring checks or partition checks are the most appropriate for monitoring the quality of data.
When the advanced profiling data quality check is run, only one sensor readout is saved per month. As an illustration, if the check is run three times in April, and one time in May the table with the results could look like this:
If there was a change in the data, and we run the check again in May, the result for May will be updated.
Checks configuration in the YAML file
Advance profiling data quality checks, like other data quality checks in DQO checks are defined as YAML files.
Below is an example of the YAML file showing sample configuration of an advanced profiling column data quality check nulls_percent.
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json apiVersion: dqo/v1 kind: table spec: target: schema_name: target_schema table_name: target_table timestamp_columns: event_timestamp_column: col_event_timestamp ingestion_timestamp_column: col_inserted_at partitioned_checks_timestamp_source: event_timestamp columns: target_column: checks: nulls: profile_nulls_percent: error: max_percent: 1.0 warning: max_percent: 5.0 fatal: max_percent: 30.0 labels: - This is the column that is analyzed for data quality issues col_event_timestamp: labels: - optional column that stores the timestamp when the event/transaction happened col_inserted_at: labels: - optional column that stores the timestamp when row was ingested
specsection contains the details of the table, including the target schema and table name.
timestamp_columns section specifies the column names for various timestamps in the data.
columns section lists the columns in the table which has configured checks. In this example the column named
target_column has a configured check
profile_nulls_percent. This means that the sensor reads the percentage of null
target_column. If the percentage exceeds a certain threshold, an error, warning, or fatal message will