Explain the ETL process in data warehousing.
Instruction: Describe what ETL (Extract, Transform, Load) is and its role in the context of data warehousing.
Updated
Official answer
ETL extracts source data, transforms it under explicit rules, and loads the destination. For an order warehouse, define one fact row per source order line and retain its source identity.
A practical incremental load captures a consistent source position, stages new and changed rows, validates required keys and amounts, resolves dimension versions, and publishes the fact changes with a durable progress marker. Missing dimensions, deletes and late corrections need documented handling. Do not treat an arrival timestamp as proof that an older source event is irrelevant.
If a worker fails after writing facts but before recording progress, replay must not create duplicate facts. Use a unique source key and a transaction or equivalent atomic publication protocol appropriate to the destination. Reject conflicting versions deliberately rather than allowing an older retry to overwrite a newer correction.
Reconcile source and target counts and amounts by stable intervals, report rejected records, and expose freshness/completeness. A successful job exit is not evidence that every source change arrived. Version transformations so a backfill is reproducible and separately validate reruns, partial failure and schema changes. ETL is a process; it does not automatically clean or reconcile data.