Data360 DQ+ v14.0 UAT & PROD release schedule announcement US/UK/AU/EU – multi-tenant environments (AWS only)
This upgrade applies exclusively to multi-tenant environments (AWS only) in the US, UK, AU, and EU regions; single-tenant and enterprise customers are not impacted by this release. Please review the schedule below to determine if your environment will be affected.
There will be a version upgrade for the following UAT and PROD environments on Friday, 10th April'26 and Saturday, 18th April'26, as per the following schedule:
UAT:
- US UAT environment: April 10th @3:00 PM CT
- EU/UK/AU UAT environments: April 10th @2:00 PM CT
PROD:
- US PROD environment: April 18th @4:00 PM CT
- EU/UK/AU PROD environments: April 18th @5:00 PM CT
What's new in this release:
Below are some of the key features new in this release. For full details about this release, including other enhancements and bug fixes, please refer to the Release Notes which will be published at launch in the Precisely help center
Process Model: Make notification emails easier to read with sorted data tables
Users can now sort data directly in the "Notify with Data Table" task node in the Process Model, making it easier to present information in a clear and meaningful order. This helps recipients review notifications more quickly and makes emails easier to interpret and act on.
Kafka data store enhancements – access to header and key
Kafka data stores now support access to both message headers and key values through the new "kafka_message_headers" and "kafka_message_key" options. Message headers are returned as base64-encoded JSON strings, and a new checkbox in the user interface lets users enable message key capture, automatically exposing the "kafka_original_key" field for SQL based‑ processing.
User management API enhancements
The GraphQL "users()" API now includes additional filtering options and returns more user attributes, giving teams greater flexibility when working with user data. New APIs also let Administrators add or remove users from groups, while the "readUser()" query makes it easier to retrieve detailed information for an individual user by login ID. These updates simplify integration with identity management systems and make it easier to manager users and group memberships programmatically.
Process Model: Keep data quality workflows running with automatic recovery
Users can now configure automatic job re‑runs directly in the Process Model settings, enabling workflows to recover automatically after a cluster failure. This help reduce downtime, improve reliability, and keep data quality processes running smoothly without manual intervention.
More Information
For any technical difficulties, visit Contact Support. You can register and/or open a support case.
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Jyotsna Sharma
*Precisely Software Inc.
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