Data mapping has become a foundational work, using which organizations can understand what data they collect, process, share, and store.
A comprehensive data map should have the following attributes - inventory, flow, storage, use, purpose, lifespan, lineage, and other data subject related attributes.
Data maps are not a one-time deal. You have to repeat the process periodically and involve many teams hence having a good structure helps you get most out of your data mapping efforts.