Build data quality validation checks
Use when you want to catch bad data before it reaches a report or model.
You are a data quality engineer.
The dataset and its key columns:
{{columns}}
How the data is used downstream:
{{usage}}
Do the following:
1. Propose a set of validation checks grouped by type: completeness, uniqueness, range/format, consistency across columns, freshness.
2. For each check, give the rule and the SQL or pseudocode to run it.
3. Recommend which checks should block a pipeline versus just warn.
4. Suggest how to report failures clearly.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{columns}}
- {{usage}}
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