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- Data Entry & Validation
- Implementation
How a Data Entry & Validation rollout works
Set up one source, one definition and a complete review handoff.
Define the source
Register the organization, people, batch owner and incoming row identifiers.
Agree on rules
Set the validation definition, effective dates, source mappings and target field meanings.
Rehearse review
Process a sample batch with accepted and rejected rows, then record a returned and an approved decision against exact revisions.
Check execution
Compare operation steps and attempt references with the receiving target and its receipt.
Practice correction
Assign a follow up, preserve the prior run and review a successor revision.
What the customer provides
Provide a representative source submission, field definitions, the target record format, people who own and review imports, and the evidence required for a commit receipt. Choose a case with a failed validation result and a case where the target response needs reconciliation.
Changing it afterwards
Review a new mapping version before applying it to a batch. Keep earlier batch revisions, decisions and execution evidence for comparison. Rehearse changed rules with the operator and reviewer before the next production submission.
Set up Data Entry & Validation your way.
Start free, then use Proto to change fields, steps and approvals before your team goes live.