Service guides / AI automation
Data quality checks · AI automationDocument expiry tracking: data quality checks
Agree what a valid source record looks like. Start with a document register and renewal intervals and plan a renewal calendar with evidence links.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- a document register and renewal intervals.
- Proposed result
- a renewal calendar with evidence links.
- A decision to resolve
- missing expiry dates and replaced documents.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check a document register and renewal intervals for completeness, conflicting versions and consistent references.
- Add a separate validation rule for missing expiry dates and replaced documents.
- Keep unresolved records separate from a renewal calendar with evidence links; record the reason rather than silently filling a gap.
Questions to answer together
- Which fields, references or measurements must be present?
- How are duplicates, contradictions and missing values reported?
- Which corrections require confirmation from the source owner?
What to have at the end
A validation checklist with examples of valid, rejected and unresolved records.
Record the decision on missing expiry dates and replaced documents alongside the source material. If it is still unresolved, identify who can answer it and what work depends on the answer.
Prepare your enquiry
Use this as a starting point. Add your current process, available examples and constraints before sharing.
Send your completed brief to hello@iansamonte.com or visit the main page to discuss your project.