Data Quality Frameworks

1---
2name: data-quality-frameworks
3description: Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
4---
5 
6# Data Quality Frameworks
7 
8Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.
9 
10## Use this skill when
11 
12- Implementing data quality checks in pipelines
13- Setting up Great Expectations validation
14- Building comprehensive dbt test suites
15- Establishing data contracts between teams
16- Monitoring data quality metrics
17- Automating data validation in CI/CD
18 
19## Do not use this skill when
20 
21- The data sources are undefined or unavailable
22- You cannot modify validation rules or schemas
23- The task is unrelated to data quality or contracts
24 
25## Instructions
26 
27- Identify critical datasets and quality dimensions.
28- Define expectations/tests and contract rules.
29- Automate validation in CI/CD and schedule checks.
30- Set alerting, ownership, and remediation steps.
31- If detailed patterns are required, open `resources/implementation-playbook.md`.
32 
33## Safety
34 
35- Avoid blocking critical pipelines without a fallback plan.
36- Handle sensitive data securely in validation outputs.
37 
38## Resources
39 
40- `resources/implementation-playbook.md` for detailed frameworks, templates, and examples.
41