Data Mapping
Batching records without losing individual failures
Use batches while tracking each record’s success, failure or unknown outcome and retrying only appropriate entries.
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Data Mapping
Data Mapping
Handling changes to a record while approval is pending
Classify edits to a record under review, preserve the terms shown and prevent stale approval from authorising changed terms.
Data Mapping
Handling optional fields in an API payload
An optional field is a contract decision, not a field to fill with a convenient blank.
Data Mapping
Identifying workflows that run without producing useful changes
Classify no-change workflow runs, find avoidable usage and protect useful checks before reducing execution.
Data Mapping
Mapping different date and timezone formats
Date mapping fails when a workflow treats every date-like string as the same kind of value.
Data Mapping
Mapping inputs and outputs before building an integration
Create an input-to-output contract for an integration, including field meaning, missing values, destination results and rejection paths.
Data Mapping
Normalising identifiers across connected applications
Two applications can refer to the same customer, order or case with different identifiers.
Data Mapping
Reading an API response before mapping fields
Inspect an API response's status, headers, JSON shape and field meaning before mapping values into a workflow.
Data Mapping
Recording source-system dependencies
Build a source dependency register for a workflow, covering events, lookups, accounts, field contracts, owners and missed-work recovery.
Data Mapping
Separating orchestration state from business records
Define which system owns business facts and which progress an orchestrator stores, including references, versions and result IDs.
Data Mapping
Workflow data mapping
Workflow data mapping defines how a value leaving one application becomes a value another application can safely use.