Catch bad data before it breaks your pipelines.
Guides creation of validation suites, data tests, and contracts that check the reliability of data pipelines.
When to use it
Use when adding pipeline quality checks, configuring validation, building dbt tests, establishing data contracts, monitoring quality, or automating validation in CI/CD.
Give it a data-quality implementation request in a project; it helps build validation suites, tests, contracts, and pipeline checks.
What you provide
The quick-start validation code runs in Python; no runtime version is specified.
The illustrated automated validation pipeline requires a configured warehouse datasource containing the tables to validate.
This skill
Slack
Sends failure notifications to Slack (irreversible)
warehouse
Reads warehouse tables for validation