Overview
Data transformation pipelines fail silently when they encounter unexpected input shapes — returning partial results, dropping malformed records, or crashing on the first invalid record without processing the valid ones. Production transformations must validate input at boundaries, accumulate all errors rather than failing at the first one, and produce transformation results that clearly distinguish successful from failed records.
The Data Transformation Patterns Framework validates at entry, transforms with type safety, and produces result sets that make failures visible and recoverable.
Key Features
Result type for explicit success/failure
Schema validation at boundaries
Single record transformation with Result
Batch transformation with error accumulation