Traditional copy data management approaches often rely on cumbersome and storage-intensive methods — such as full data replication — to create multiple copies of data for various purposes like machine learning, AI agents, backups, testing, development, and analytics. However, these conventional methods can lead to significant storage overhead, increased costs, and complexity in managing multiple data copies.