Валидация данных с Great Expectations и dbt

★ 8.5 · data

data-quality-frameworks is a Claude Code skill that implements data quality validation using Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines. It covers six quality dimensions — completeness, uniqueness, validity, accuracy, consistency, and timeliness — each mapped to concrete expectations like `expect_column_values_to_not_be_null` and `expect_column_pair_values_A_to_be_greater_than_B`. The skill includes a data testing pyramid (schema, unit, and integration layers), Great Expectations project setup via CLI, checkpoint-based validation, and patterns for establishing data contracts between teams. Built for data engineers who need to automate quality checks in CI/CD pipelines and fail builds when critical tables don't pass validation.