The challenge
A large, multi-stream data collection initiative faced significant quality risks.
The data was intended to support high-stakes external reporting, but complex anomalies across source systems threatened the validity of the resulting insights. Without remediation, stakeholders could not rely on the dataset as a defensible evidence base.
What we did
We led a mission-critical data governance and repair project, using R and SQL to perform deep system analysis across the affected datasets.
The work identified structural inconsistencies, reconciled conflicting records, and resolved complex anomalies that standard reporting checks had not surfaced. Governance controls were strengthened so repaired data could be traced, validated, and reused with confidence.
Outcome
The project delivered a high-integrity single source of truth for the reporting programme.
The resulting insights were statistically robust, operationally explainable, and able to meet the rigorous standards required for national-level reporting and external stakeholder scrutiny.