Service guides / SaaS development
Data quality checks · SaaS developmentProject workspaces: data quality checks
Agree what a valid source record looks like. Start with sample projects and collaborator roles and plan a project setup and task handover journey.
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The project in view
- Start with
- sample projects and collaborator roles.
- Proposed result
- a project setup and task handover journey.
- A decision to resolve
- removed collaborators retaining access.
This is a planning example. It does not describe a completed client engagement.
Data quality checks for this project
- Check sample projects and collaborator roles for completeness, conflicting versions and consistent references.
- Add a separate validation rule for removed collaborators retaining access.
- Keep unresolved records separate from a project setup and task handover 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 removed collaborators retaining access 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.