Metadata is usually split three ways. Business metadata is meaning — the definition of "active customer", the owner, the sensitivity classification. Technical metadata is structure — table, column, type, nullability, the job that populates it. Operational metadata is behavior — when the load last ran, how many rows arrived, how many failed validation. A governance program needs all three, but it only ever has budget to start with one.
In practice. Start with business metadata for the data that already appears in decisions, because that is where the absence hurts: an analyst who cannot tell which of two revenue columns is the reported one is losing an hour a week to something a sentence would fix.
Where it goes wrong. Metadata is harvested wholesale because a tool can do it automatically, which yields a catalog of 40,000 technical entries with no meaning attached. Automated harvesting is the cheap half. The expensive half is a human deciding what each thing means, and no tool has ever done that part.