Manage Policies by Name
These APIs let you manage an existing Data Quality policy using its name instead of the numeric ID.
This is useful in automated workflows or CI/CD pipelines where the policy name is stable and easier to reference than its internal ID.
Endpoint(s)
Path Parameters
| Name | Type | Required | Description |
|---|---|---|---|
| name | string | Yes | Unique name of the Data Quality policy. |
Sample Request
Manage a Data Quality policy by name
curl -X PUT "https://{HOST}/catalog-server/api/rules/data-quality/byName/Customer_DQ_Policy" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $TOKEN" \ -H "accessKey: $ACCESS_KEY" \ -H "secretKey: $SECRET_KEY" \ -d '{ "description": "Updated DQ policy to check for null values and pattern mismatches on critical columns.", "status": "ACTIVE", "scheduled": true, "schedule": "0 2 * * *", "rules": [ { "columnName": "email", "measurementType": "NULL_VALUES", "threshold": 0 }, { "columnName": "email", "measurementType": "PATTERN_MISMATCH", "pattern": "^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Za-z]{2,}$" }, { "columnName": "country_code", "measurementType": "REFERENCE_CHECK", "referenceDataset": "valid_country_codes" } ], "tags": ["customer", "critical", "data-quality"] }'What this does:
Updates an existing Data Quality policy named
Customer_DQ_Policy.Schedules it to run daily at 2 AM (
0 2 * * *).Adds multiple DQ rules including:
- Null check
- Pattern validation
- Reference check
Attaches descriptive tags.
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