Data Import/Export Guide: Validate, Log, and Retry
Build reliable data import and export pipelines: validate schemas, handle encoding, log errors per row, and retry partial failures safely.
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Tags: data, pipelines, best-practices
Data Import/Export Guide: Best Practices for Reliable Data Pipelines Most data import/export bugs aren't interesting bugs — they're the same failures that happen every time: a file with the wrong encoding, a NULL that should be a zero, a schema that changed upstream, a duplicate row that got imported twice. This guide covers the production patterns that prevent these failures: validation on import, idempotent designs, staging tables, checksums for large files, and error reporting that tells you what went wrong without requiring you to dig through logs. --- Validate Before You Process The most important rule: validate your data before you process it, not during. Processing catches the first error and stops. Validation collects all errors and reports them together. Schema Validation Define…
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