Service guides / SaaS development
Data quality checks · SaaS developmentQuality inspections: data quality checks
Agree what a valid source record looks like. Start with inspection forms and issue categories and plan an inspection-to-corrective-action workflow.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- inspection forms and issue categories.
- Proposed result
- an inspection-to-corrective-action workflow.
- A decision to resolve
- revising evidence after an issue is closed.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check inspection forms and issue categories for completeness, conflicting versions and consistent references.
- Add a separate validation rule for revising evidence after an issue is closed.
- Keep unresolved records separate from an inspection-to-corrective-action workflow; 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 revising evidence after an issue is closed 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.