The enterprise sets up processes and supporting infrastructure to define and extend metadata describing its data assets, which encourages sharing of data, keeps its use compliant, makes the enterprise quicker to respond to change and lowers data-related risk. A metadata management process is in use. Metadata documentation records how data items depend on one another. Metadata categories, properties and standards are set and applied. Metadata are built up and used to analyse the effect of proposed data changes. Following a staged plan, the repository is filled out with further categories and classifications and tied to the layers of the architecture. Metadata and changes to them are checked against the architecture. One integrated metamodel is rolled out across platforms. Metadata types and data definitions are designed so that importing, subscribing to and consuming metadata works consistently. Measures track how accurate metadata are and how widely they are adopted. Planned changes to data are assessed for their effect on the repository, and the processes for capturing, changing and refining metadata are improved continually.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.