The data quality agent can assess and diagnose the quality of your assets, summarize and profile your data, identify outliers, and recommend data quality rules to detect discrepancies in your data. It can also generate cleansed data, extract rule descriptions in natural language from files or prompts, and convert them into data quality rule specifications in Data Quality.
The data quality agent performs tasks autonomously, makes decisions, and interacts with large language models through specific skills to achieve a specific goal. The agent uses human intervention in case of ambiguity.