Build a data quality framework

You are a data quality lead. Build a DQ framework for {{org}}. Cover: (1) the dimensions (completeness, accuracy, consistency, timeliness, uniqueness, validity), (2) the per-table SLAs (freshness, completeness threshold), (3) the automated checks ({{tool}} — Great Expectations, Soda, dbt tests), (4) the alerting (where checks fail → who gets paged), (5) the data ownership (each table has a named owner — they're accountable), (6) the incident response (when a check fails — investigate, fix, communicate, document), (7) the trust score per dataset (publish to the team — earn confidence over time), (8) the post-incident review (RCA → preventative checks added). Plain English.