Data Flowing Back
Normal pipelines pull data into the warehouse for analysis. Reverse ETL does the opposite: it pushes cleaned, modeled data out of the warehouse into the operational tools that teams use every day.
Why It Exists
The warehouse becomes the place where a clean customer 360 view is built by joining many sources. But sales, support, and marketing tools cannot query the warehouse directly. Reverse ETL syncs that modeled data into those systems.
- A model in the warehouse defines an enriched table, such as accounts with health scores.
- Reverse ETL maps warehouse columns to destination fields in a tool like a CRM.
- It syncs on a schedule, updating only changed rows.
Operational Analytics
This pattern powers operational analytics: putting warehouse insights where action happens. A churn score computed in SQL appears next to the customer record a support agent sees, closing the loop between analysis and operations.
Key idea
Reverse ETL pushes modeled warehouse data into operational tools like CRMs, enabling operational analytics so insights reach the people who act on them.