From Data Quality to Quality of Agentic Data Use: A Conceptual Framework for Agentic Data Engineering
Large language models and AI agents are extending data-engineering automation beyond isolated artifact generation toward end-to-end processes in which agents interpret requirements, select data, generate transformations, invoke tools, validate results, and communicate analytical outputs. This shift introduces risks tha...