Getting Started with Promote

Promote is an operation that copies data quality assets from a source location to a destination location within the Qualytics platform. It acts as a replication mechanism for quality checks, computed fields, computed tables, and computed files — enabling you to build quality rules once and apply them across your data ecosystem.

In this section you will learn the role promote plays in data quality, how it supports standardization and change management across environments, practical scenarios for each promote type, and best practices for safe rollouts. Every promote type uses the same access gate: Editor team permission on both the source and the destination — see Permissions for details.

The Role of Promote in Data Quality

In any data quality program, teams need to apply consistent rules across multiple datasets. A quality check that validates email formats in one table should work the same way in every table that contains email addresses. A computed field that normalizes dates should produce the same transformation wherever it's used.

Rather than recreating these assets manually in each location, Qualytics uses promote to:

• Distribute quality standards — Promote quality checks from a reference container to every container that shares the same field structure, ensuring uniform validation rules.
• Replicate transformations — Promote computed fields, tables, and files from one environment to another, keeping derived data consistent across datastores.
• Push updates downstream — When a quality check is refined at the source, re-promoting it finds the destination produced by the previous promotion and updates it in place. See Entity Matching.
• Enable environment workflows — Build and test quality rules in development, then promote them to staging and production with confidence.

How Promote Supports Data Quality

Standardized Quality Rules

By promoting quality checks from a reference container to other containers, you ensure that the same validation rules apply everywhere. This eliminates drift between environments and reduces the risk of inconsistent quality standards.

For example, if your team maintains a set of quality checks on a canonical customers table, you can promote those checks to every customers table across your datastores — development, staging, and production.

Efficient Computed Asset Management

Computed fields, tables, and files often represent significant engineering effort. Promote allows you to define these assets once and replicate them wherever they're needed, avoiding redundant work and ensuring that all environments use the same transformation logic.

Change Management

When you update a quality check or computed field at the source, re-promoting it to the same destination updates the existing entity rather than creating a duplicate. The platform looks up the destination produced by the previous promotion and updates it in place — even if it has been renamed since. See Entity Matching for the full strategy.

Audit Trail

Every promote operation records detailed metadata — which entities were promoted, from where to where, what the result was (created, updated, skipped, or failed), and who triggered the operation. This provides a clear audit trail for compliance and troubleshooting.

Operation Lifecycle

Promote runs asynchronously through a background worker, and the platform makes guarantees about how an operation behaves through its lifetime:

• Resumable on retry — If the background worker is interrupted and the operation is retried, the platform skips entities that have already been processed. Previous failed results for the same entity are replaced by the new attempt rather than duplicated. You will not see double-promotion or partial duplicates from a worker restart.
• Abortable mid-run — A running promote operation can be aborted from the Activity page. The worker stops cleanly between entities — already-processed entities keep their result, and the operation is marked as aborted.
• Per-entity failures do not stop the operation — A promotion is reported as success if at least one entity is created, updated, or skipped. Individual entity failures are surfaced in the per-entity result list. The operation only reports failure when every entity in the request fails.
• Source and destination must differ — A promote request returns an error if the source and destination resolve to the same container or datastore.

Practical Scenarios

For concrete data engineering scenarios — multi-tenant onboarding, environment rollouts, warehouse migrations, schema versioning, cross-region replication, and DFS standardization — see the Use Cases page.

Best Practices

Practice	Rationale
Use Draft mode for quality checks	Promoting checks as Draft allows you to review and validate them before they run on the destination. This is especially important when promoting to production environments.
Use tags to organize promotions	Tag your quality checks and computed fields by purpose (e.g., pii-checks, financial-rules) so you can promote related assets together using tag-based selection.
Re-promote after source changes	When you update a quality check or computed field at the source, re-promote it to push the changes to all destinations. Re-promotion finds the existing destination and updates it in place, rather than creating a duplicate.
Verify source fields exist on the destination	For computed field promotions, ensure the destination container has the required source fields. Missing source fields will cause the promotion to fail for those computed fields.
Use auto-match for computed files	When promoting computed files, use the auto-match feature to quickly map source files to destination file patterns. Review the confidence scores and adjust manually if needed.
Review promotion results	Always check the promotion results to verify that all entities were successfully promoted. Failed promotions may indicate schema mismatches or naming conflicts.