Scoping
Clarify the decision, data journey, concern and boundaries.
Control-led approach
Start with the expected outcome. Trace backward to the data and controls that make it defensible.
DQIntegrity—Data Quality & Integrity—combines data-journey analysis, control architecture, evidence challenge and practical remediation. The method is designed for complex environments where ownership and failure modes cross systems, functions, entities and providers.
How an engagement begins
A clear route from first discussion to defensible next action.
The opening sequence is deliberately simple. It establishes the decision and boundaries, examines the available evidence, diagnoses where integrity breaks down, and agrees the proportionate next step.
Evidence
Identify and review the available artefacts, controls, mappings and records.
Diagnosis
Determine where completeness, correctness, traceability or control evidence breaks down.
Decision
Agree findings, priorities and the most appropriate next action.
Principal-led, confidential and focused
The first discussion determines fit and proportionate scope—not a larger programme before the evidence supports one.
Visual framework
From Data Integrity Diagnosis to Defensible Outcomes
The practical route from structural exposure to proof, control design, remediation assurance and sustainable ownership.
Six stages
A structured route from uncertainty to sustainable control.
Decision and expected population
Clarify the business or control decision, the complete population required and material critical-data elements.
End-to-end data journey
Trace source, movement, transformation, enrichment, storage, consumption and output.
Failure modes and assumptions
Test where records can disappear, duplicate, change meaning, arrive late or bypass expected controls.
Preventive and detective architecture
Design reconciliations, correctness tests, thresholds, exception routes and ownership.
Operation and accountability
Determine whether control execution, investigation, escalation and remediation can be demonstrated.
Sustainable monitoring
Integrate reporting, governance, root-cause treatment and change control into the operating model.
What DQIntegrity does not do
Clear positioning protects independence.
DQIntegrity provides
- Independent diagnosis and control challenge
- Requirements and control architecture
- Assurance of delivery and evidence
- Remediation planning and senior reporting
- Retained Senior Data Quality & Integrity Advisory
DQIntegrity does not claim
- To replace legal, audit or regulated advice
- To be a software product or data-quality tool
- To certify AI models or regulatory compliance
- To own client decisions or final regulatory submissions
- To provide unlimited staff augmentation
Control confidence should be evidenced.