Construction data cleansing
We clean the data behind the golden thread: duplicates removed, formats standardised, gaps flagged, and asset and register data reconciled, so what you migrate or hand over is accurate enough to rely on.
Why construction data needs cleansing
Asset registers, drawing registers, compliance trackers and handover datasets accumulate duplicates, inconsistent formats and silent gaps: the same asset listed three ways, dates in different formats, warranty fields empty. When that data feeds the golden thread or migrates into a new CDE, the errors migrate with it.
We clean the data before it moves: de-duplication, standardisation, gap-flagging and validation, with machine-learning-assisted detection and human review on everything that matters.
Scope of the work
- De-duplication - duplicate assets and records identified and merged, with the audit trail kept
- Standardisation - names, dates, locations and formats reconciled to one convention
- Gap-flagging - missing fields flagged and categorised, not silently filled
- Cross-register reconciliation - asset register, drawing register and certificate tracker matched to each other
- Validation - machine-learning-assisted error detection with human review
- Delivery - clean dataset, error report and a data quality scorecard
Where this connects
- Migration without contamination - clean data goes into the CDE, not the mess
- Registers you can rely on - the asset register is only evidence if it is accurate
- Safety case credibility - contradictions between registers undermine the whole case
- Defensible data - the error report shows what was wrong and what was done
How your data is handled
UK GDPR and DPA 2018 compliant, no third-party sharing, kept secure and access-controlled, handled by vetted NDA-bound staff. See our security and compliance page for details.
Questions, answered
What kind of data do you clean?
Registers and datasets: asset registers, drawing registers, compliance certificate trackers, maintenance schedules, handover spreadsheets and CDE exports. If it is structured data that feeds the golden thread, we clean it.
Do you ever delete data?
Only with your explicit instruction. Duplicates are identified and merged with the audit trail kept, and we flag anything we recommend removing rather than deleting it ourselves. The error report records every change.
How do you find duplicates in asset registers?
Machine-learning-assisted matching on IDs, locations and descriptions, with human review of anything uncertain. We merge carefully: the same asset listed three ways becomes one record, with the variants documented.
What is in the data quality scorecard?
A per-field view of completeness, consistency and duplication before and after cleansing, so you can see the state of the data and demonstrate the improvement. It doubles as evidence of reasonable data management.
Can you clean data before a CDE migration?
Yes, that is a common trigger: clean and reconcile first, then migrate, so the new system starts with data you can rely on. We can also do the migration and structure work as part of the same engagement.
Related guides
- What is the golden thread? - the requirement and who it applies to
- Golden thread asset register - the register this service cleans
- CDE data entry - clean data, then upload it
Need help putting this into practice?
We process, structure and validate golden thread records so they answer the regulator's questions. Every project is scoped and quoted individually.