You're working on a data pipeline where source data can arrive with missing fields, duplicate records, or conflicting values across systems. You want a practical approach for keeping downstream reporting usable while preserving traceability back to the raw inputs.
How would you handle a dataset that is incomplete or inconsistent?
Data quality controls for missing and inconsistent recordsETL design for validation, quarantine, and remediationIdempotent loading to avoid duplicate downstream dataBackfill and replay strategy after source corrections