Generate schema YAML tests and custom checks for dbt models.
npx skills add https://github.com/clawdata/clawdata --skill data-quality-clawdata
Please help me install this Agent Skill. Skill: data-quality Source: https://github.com/clawdata/clawdata/tree/main/skills/data-quality Command: npx skills add https://github.com/clawdata/clawdata --skill data-quality-clawdata
Add data quality checks and tests to dbt models and pipelines to ensure data integrity and reliable analytics.
Run the data-quality workflow to analyze your dbt project and generate tests for staging models.
High-intent search queries and answers about installing and using this skill.
To add data quality tests to dbt models, generate schema YAML files with built-in checks like unique, not_null, relationships, and accepted_values to validate data integrity across staging and marts.
Automating dbt data validation involves applying generic tests in schema YAML and creating custom tests or macros for advanced checks, ensuring pipeline data integrity and trust in analytics.
Yes, you can leverage dbt_utils and dbt_expectations for advanced dbt schema testing when generic checks are insufficient, enabling complex data validations and source freshness checks.
You need custom dbt tests when generic schema YAML checks cannot capture specific business rules, requiring you to write custom SQL queries in the tests directory or via macros.
Yes, dbt data quality testing supports source freshness checks to validate that your source data is up to date, adding an essential layer of trust to your analytics pipelines.
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