# Reverse ETL and Data Observability: Solving Data's "Last Mile" Problem

DevFeed: [Reverse ETL and Data Observability: Solving Data's "Last Mile" Problem](<https://devfeed.tech/articles/reverse-etl-and-data-observability-solving-data-s-last-mile-problem-83123.md>)

Original publisher: [Read original article](<https://montecarlo.ai/blog-reverse-etl-and-data-observability>)

Author: Barr Moses

Published: 2021-09-08T15:03:57Z

Content type: article

Language: en

Sources: [Monte Carlo](<https://devfeed.tech/sources/monte-carlo.md>)

Topics: [observability](<https://devfeed.tech/topics/observability.md>), [data observability](<https://devfeed.tech/topics/data-observability.md>), [etl](<https://devfeed.tech/topics/etl.md>)

Tags: [data](<https://devfeed.tech/tags/data.md>), [data-observability](<https://devfeed.tech/tags/data-observability.md>), [data-observability-data-platforms](<https://devfeed.tech/tags/data-observability-data-platforms.md>), [data-platforms](<https://devfeed.tech/tags/data-platforms.md>), [observability](<https://devfeed.tech/tags/observability.md>), [reverse-etl](<https://devfeed.tech/tags/reverse-etl.md>)

## AI overview

The article explains how Reverse ETL moves transformed warehouse data into operational business tools, making it usable in teams' workflows. It describes data observability practices--including monitoring freshness, distribution, volume, schema, and lineage--to detect data quality problems and help teams investigate pipeline issues before they affect downstream users.

## Source excerpt

How Reverse ETL and Data Observability can help teams go the extra mile when it comes to trusting your data products.