Service guides / SaaS development
Data quality checks · SaaS developmentInventory management: data quality checks
Agree what a valid source record looks like. Start with product records and stock movement examples and plan a stock receiving-to-dispatch workflow.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- product records and stock movement examples.
- Proposed result
- a stock receiving-to-dispatch workflow.
- A decision to resolve
- adjustments with no audit trail.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check product records and stock movement examples for completeness, conflicting versions and consistent references.
- Add a separate validation rule for adjustments with no audit trail.
- Keep unresolved records separate from a stock receiving-to-dispatch 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 adjustments with no audit trail 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.