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Data quality checks · Web & mobile appsStaff directories: data quality checks
Agree what a valid source record looks like. Start with approved staff fields and visibility rules and plan an accessible team lookup tool.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- approved staff fields and visibility rules.
- Proposed result
- an accessible team lookup tool.
- A decision to resolve
- exposing private contact information.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check approved staff fields and visibility rules for completeness, conflicting versions and consistent references.
- Add a separate validation rule for exposing private contact information.
- Keep unresolved records separate from an accessible team lookup tool; 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 exposing private contact information 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.