# Monte Carlo and dbt Labs Announce Partnership to Help Analytics Engineering Teams Achieve More Reliable Data

DevFeed: [Monte Carlo and dbt Labs Announce Partnership to Help Analytics Engineering Teams Achieve More Reliable Data](<https://devfeed.tech/articles/monte-carlo-and-dbt-labs-announce-partnership-to-help-analytics-engineering-teams-achieve-more-reliable-data-83085.md>)

Original publisher: [Read original article](<https://montecarlo.ai/blog-monte-carlo-and-dbt-labs-announce-partnership-to-help-analytics-engineering-teams-achieve-more-reliable-data>)

Author: Matt Sulkis

Published: 2022-08-16T15:44:00Z

Content type: news

Language: en

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

Topics: [data observability](<https://devfeed.tech/topics/data-observability.md>), [CI/CD](<https://devfeed.tech/topics/cicd.md>), [schema-evolution](<https://devfeed.tech/topics/schema-evolution.md>), [product analytics](<https://devfeed.tech/topics/product-analytics.md>)

Tags: [analytics-engineering-teams](<https://devfeed.tech/tags/analytics-engineering-teams.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [ci-cd](<https://devfeed.tech/tags/ci-cd.md>), [code](<https://devfeed.tech/tags/code.md>), [data-observability](<https://devfeed.tech/tags/data-observability.md>), [data-pipelines](<https://devfeed.tech/tags/data-pipelines.md>), [dbt](<https://devfeed.tech/tags/dbt.md>)

## AI overview

Monte Carlo and dbt Labs announce an expanded partnership and integration aimed at improving data reliability. The integration surfaces dbt test failures and model errors as incidents, supports monitoring for freshness, distribution, volume, and schema changes, and links dbt models with database tables and metadata. The article describes how the tools combine testing and data observability to help data teams investigate data quality issues.

## Source excerpt

When it comes to trusting your data, Monte Carlo, the creator of the data observability category, and dbt Labs, creators of dbt, are better together. "Why didn't my job run?" "What happened to this dashboard?" "Why is this column missing?" "What went wrong with my data?!" If you've been on the receiving end of a ...