You can establish data quality criteria for your data set, create data quality rule occurrences for the data elements in your catalog, and ensure that the data meets high standards of quality with the help of the data quality rule recommendation skill of the data quality agent.
The assets for which you want to generate rules might not have associated rule templates. If there are no data quality rule templates associated with the assets, CLAIRE GPT recommends rules directly from the rule specifications in Data Quality.
You can get rules for datasets that don't have manually created or associated rules. You can then use the recommended rules to establish data quality criteria for your data set. By defining the criteria, you set standards for accuracy, completeness, and consistency of your data. You can accept or reject rule recommendations. If you accept a rule recommendation, a rule occurrence is then created for the data elements in Data Governance and Catalog, where you can review your data for discrepancies.