System for Routing Data Quality Errors to a Root Cause Queue

The problem

In day-to-day operations, quality tests, schemas and the ownership catalogue are held in separate records and files, preventing the team from reviewing the same case in a single view.

As a result, the link to source evidence can be lost while preparing an issue category and owner recommendation, leading to repeated checks and uncertainty about the basis for the decision.

Incomplete automation may overlook errors spanning multiple sources, while poorly controlled automation risks an incorrect bulk correction.

What we set out to improve

• Time required to prepare an issue category and owner recommendation for review
• Correct routing of errors spanning multiple sources to the appropriate specialist queue
• Recording of recommendations corrected or rejected by the data owner

How the system works

1. 01 Retrieve quality test, schema and ownership catalogue data from an authorised source
2. 02 Verify the source system, record identifier and recency information
3. 03 Transform the fields into the target process schema
4. 04 Prepare an issue category and owner recommendation draft
5. 05 Compare the draft with business rules and source records
6. 06 Check for exceptions where an error spans multiple sources
7. 07 Obtain the data owner's approval, correction or rejection
8. 08 Write the input, recommendation, changes and final decision to the audit log

Methods we used

• Source-traceable data extraction from quality tests, schemas and the ownership catalogue
• Structured output that restricts issue category and owner recommendation fields through business rules
• An exception gate that separates errors spanning multiple sources
• A queue that shows the source and recommendation together for the data owner
• Duplicate-processing controls and rollback records to mitigate the risk of an incorrect bulk correction

Where people stay involved

Data and security

Only the fields required for the task are processed from quality tests, schemas and the ownership catalogue. Source-system permissions remain in force, and personal or commercially sensitive data is minimised before being provided to the model. Every read, recommendation, human amendment and write to the target system is logged.

Who this suits

Frequently asked questions