Service guides / SaaS development
Data quality checks · SaaS developmentExpense approvals: data quality checks
Agree what a valid source record looks like. Start with redacted expenses and approval thresholds and plan an expense submission-to-review journey.
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The project in view
- Start with
- redacted expenses and approval thresholds.
- Proposed result
- an expense submission-to-review journey.
- A decision to resolve
- self-approval and duplicate reimbursement.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check redacted expenses and approval thresholds for completeness, conflicting versions and consistent references.
- Add a separate validation rule for self-approval and duplicate reimbursement.
- Keep unresolved records separate from an expense submission-to-review journey; 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 self-approval and duplicate reimbursement 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.
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