An enterprise-wide, integrated data quality strategy is set to reach and then keep the degree of data quality (complexity, integrity, accuracy, completeness, validity, traceability, timeliness) that business goals depend on. Business and technology stakeholders shape the strategy together; executive management approves it, and it is actively managed so the enterprise moves from where it is today toward the intended target. It is applied throughout the enterprise through matching policies, processes and guidelines. Its policies, processes and governance are embedded across the whole data life cycle, and the corresponding processes are made mandatory within the development life cycle. A sequenced improvement plan for data quality is drawn up, tracked and kept current, and plans are checked against the strategy's goals. Data quality issues reported by stakeholders are gathered systematically, and what stakeholders expect is written into the strategy and measured.
This control maps to 1 controls across 1 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.
The graph holds this control, the 1 it maps to, and the evidence behind each claim, over MCP and REST.