ELT (Extract, Load, Transform)

A practical example

Example: a team loads raw CRM and ad-platform data into a warehouse, then builds a blended pipeline-cost model in SQL.

When the attribution definition changes, they rerun transformations on the same raw data without re-extracting from sources.

What to evaluate before investing

• Confirm the tool supports incremental loads, not just full refreshes, so large tables stay manageable.
• Check which destinations are supported natively and whether transformations run in-warehouse or on separate compute.
• Ask how schema changes in sources, like a renamed field, are detected and handled.

Limitations and tradeoffs

Tradeoff: ELT requires a capable destination warehouse and shifts transformation cost to query compute, which can grow expensive at scale.