data-quality-frameworks

Automate data quality validation across ETL pipelines by defining expectation suites and executing checkpoints to catch issues early. This framework standardizes checks for completeness, accuracy, and freshness during data releases.

Data contracts are enforceable agreements between teams that define expected schemas to prevent schema drift. Contract-driven governance guarantees reliable data by standardizing structure and validation rules across pipelines.

Yes, you can run dbt tests and Great Expectations together in CI/CD. Integrating these validations during deployments automates data quality checks and ensures traceability before data releases.

Validate data completeness and freshness in ELT workflows by applying automated expectation suites and checkpoints. This pipeline validation ensures accuracy and reliability across tables before downstream use.

Yes, this framework supports contract-driven governance for large ETL/ELT pipelines. It enforces data contracts and executes validations to guarantee completeness, accuracy, and freshness at scale.

Use data contracts instead of standard pipeline tests when you need strict governance to prevent schema drift between teams. Contracts enforce structural agreements, while standard tests validate data values and freshness.