Data Quality & Validation
Ensure data quality meets regulatory standards or when stakeholders question the accuracy of your reports.
Prompt Template
Analyze [TABLE/PIPELINE] for data quality issues:- Check for nulls, duplicates, and anomalies- Validate against business rules: [RULES]- Suggest data quality checks to add- Recommend alerting thresholds
Industry Example
Analyze BANKING.TRANSACTIONS.DAILY_WIRE_TRANSFERS for data quality issues:- Check for nulls, duplicates, and anomalies in transaction_amount and routing_number fields- Validate against business rules: All amounts must be positive, routing numbers must be 9 digits, transaction dates cannot be future-dated- Suggest data quality checks to add to our compliance pipeline- Recommend alerting thresholds for suspicious transaction patterns (amounts over $50,000)