Because data from many sources carries risks to quality, validity, reliability and consistency and complex ETL is error-prone, the organisation uses or establishes a central data repository, validates format consistency, obtains assurance of the reliability, representativeness and relevance of data, standardises training data annotation with comprehensive guidelines, completes a standard data documentation process, keeps ETL transparent through scripting, and builds error handling into the ETL solution.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.