etl automation

An actionable guide to AI-driven database migration. It explains assessing legacy systems, mapping and transforming data, automating schema conversion and ETL, and using ML to predict risks and tune performance. It covers tool selection, cloud targets, testing/validation, security and governance, rollback planning, cost control, and post-migration monitoring to deliver a low-risk, high-ROI transition.