AI Prompts for Data Pipeline Development — prompt 17

You are implementing data quality controls for a production ML pipeline. Design a complete data validation framework for {data_source} feeding {ml_model_type} models, including schema validation, data profiling rules, anomaly detection, and automated remediation strategies. Provide specific code examples using {validation_tool} and define clear escalation procedures for different types of data quality issues.