Join the team from Moody's Analytics as they take you on a personal journey of optimizing their data pipelines for data quality and governance. Like many data practitioners, Ryan understands the frustration and anxiety that comes with accidentally introducing bad code into production pipelines—he's spent countless hours putting out fires caused by these unexpected changes. In this session, Ryan will recount his experiences with a previous data stack that lacked standardized testing methods and visibility into the impact of code changes on production data. He'll also share how their new data stack is safeguarded by Datafold's data diffing and continuous integration (CI) capabilities, which enables his team to work with greater confidence, peace of mind, and speed.

A significant proportion of dbt Cloud users do not have a dbt CI job set up. Among those who do, many don’t leverage powerful functionality like state comparison and deferral to implement Slim CI, likely causing teams to miss errors and building unnecessary tables. Setting up Slim CI in dbt Cloud can be especially challenging for larger-scale data organizations who have multiple data environments, git branches, and targets. Watch this session to learn how you can build and evolve a strong, lasting data environment using Slim CI.

Speakers: Leo Folsom, Solutions Engineer, Datafold

Register for Coalesce at https://coalesce.getdbt.com