What happens if you try to restore a dataset that is older than two versions?

When a dataset is older than two versions, it may not be restorable due to limitations set in the system for data management or archival practices. Many platforms enforce these restrictions to manage storage effectively and maintain data integrity. Over time, as new versions are created and older ones become obsolete, the system may archive or even delete older versions, making them unrecoverable for users. This ensures that only the most relevant and recent data is kept readily accessible, while older versions that are rarely accessed are either moved to deep storage or purged entirely, thus safeguarding against clutter and potential confusion in accessing data. Only the most recent versions remain intact and easily restorable, reinforcing the dependency on keeping datasets up-to-date for active analysis and decision-making.