Ataccama Data Quality Gates Release Notes

UDF conflict detection now uses parameterized queries when checking for existing functions in Snowflake, preventing potential query errors during deployment.

Security fixes.

Firewall filtering with AQL and Python: Filter which firewalls are deployed as UDFs using Ataccama Query Language (AQL) expressions or custom Python logic. Deploy only the firewalls relevant to specific pipelines or environments instead of deploying all available firewalls.

UDF naming conflict handling: DQ Gates now detects and reports conflicts when firewall names would result in duplicate UDF names in Snowflake. Resolve conflicts before deployment to prevent overwriting existing functions.

Python 3.13 support: DQ Gates now supports Python 3.13.

Support for all deployment types: DQ Gates now supports Custom Ataccama Cloud and self-managed, on-premise deployments, including environments with custom URLs for Ataccama services. Previously, only Ataccama Cloud deployments were supported.

Checking for unsupported functions is now correctly case-insensitive.

Stop poor quality data at the source: Validate and block invalid records in-flight, before they reach production. Prevent corrupted dashboards, false alarms, and downstream issues.

Deploy once, use everywhere: Transform DQ firewalls into native Snowflake UDFs callable directly in SQL. No custom code required.

Maintain control: Business users define rules in ONE, engineers integrate them into pipelines without rule management overhead. Ensure consistent data quality across platforms, even as rules evolve.

Filter invalid records in data pipelines before downstream processing.

Flag quality issues while preserving full datasets for investigation.

Implement circuit breakers that halt processing when quality drops.

Track data quality trends and generate reports from evaluation results.

Integrate validation into testing frameworks (such as dbt) and CI/CD pipelines.