Lineage
Track source → transformation → output.
DATA, RISK & PERFORMANCE
Traceable data from source to reporting output.
Make important reporting and operational outputs traceable to approved sources, transformations, definitions, rule versions, quality checks and responsible review owners.
Overview
Data lineage and quality provide the control foundation behind reliable operating and reporting information. Kelton helps connect material fields to approved sources, transformations, definitions, rule versions and review evidence, while quality controls identify missing, stale or inconsistent information before it reaches downstream workflows.
Our capabilities
Quality rules
Apply completeness, timeliness, format and cross-source consistency checks.
Definition registry
Maintain the approved definition, source and accountable owner for each critical field.
Change history
Version data mappings, transformation rules and effective dates through controlled change.
Quality dashboard
Expose data-quality exceptions, materiality, ownership and confidence in downstream outputs.
Service coverage
Core records
- Source metadata
- Mappings
- Transformation rules
- Output fields
- Review history
Operating activities
| Step | Activity | What happens |
|---|---|---|
| 1 | Register | Catalogue source/definition. |
| 2 | Track | Record transformations. |
| 3 | Test | Run quality checks. |
| 4 | Flag | Create exceptions. |
| 5 | Review | Approve changes. |
| 6 | Publish | Expose lineage with output. |
Reporting and oversight
- Lineage graph/register
- Quality score/exception report
- Definition dictionary
- Change log
What clients gain
Transparent data lineage
Connect material fields and outputs to their approved source, transformation and review history.
Earlier quality issues
Identify missing, stale, inconsistent or late information before it reaches downstream processes.
Clear ownership
Maintain agreed meaning, ownership and permitted use for critical operating fields.
Stronger reporting confidence
Preserve version history across mappings, rules and data transformations.
Governance and integration
Data Lineage & Quality is delivered through defined responsibilities, controlled records and documented review. Material exceptions, judgements and approvals remain visible and attributable throughout the operating process.
- No silent transformations.
- Version/effective date.
- Source ownership.
- Quality exception escalation.
Expertise and delivery
Experts behind the service.
Relevant professionals support service design, exception review and delivery governance where specialist judgement is required.
Meet our Experts & ProfessionalsTechnology that supports control.
Controlled data, workflow and review capabilities support consistent execution, transparent oversight and traceable evidence.
Explore Technology & ExpertiseConfigured around your operating model.
Services can be delivered through managed operations, technology enablement, co-sourced delivery or transition support.
See How We WorkFrequently asked questions
Why is lineage important for AI?
It allows users/reviewers to trace an output to approved sources and rules instead of trusting opaque model text.
Is a quality score enough?
No; material exceptions and source limitations should be visible and reviewable.
Discuss Data Lineage & Quality
Start with one workflow, one operating issue or one provider transition. We will map the current process, responsibility boundaries, required data and a practical first engagement.