Service guides / SaaS development
Data quality checks · SaaS developmentJob management: data quality checks
Agree what a valid source record looks like. Start with job cards and team assignment rules and plan a job intake-to-completion workflow.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- job cards and team assignment rules.
- Proposed result
- a job intake-to-completion workflow.
- A decision to resolve
- unassigned work disappearing from reports.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check job cards and team assignment rules for completeness, conflicting versions and consistent references.
- Add a separate validation rule for unassigned work disappearing from reports.
- Keep unresolved records separate from a job intake-to-completion 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 unassigned work disappearing from reports 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.