This covers the operational side of data quality programs in financial services: how to set up golden source designations, write validation rules for pricing and client data, build exception management workflows, and track data lineage for regulations like BCBS 239. It walks through the six quality dimensions (accuracy, completeness, timeliness, consistency, validity, uniqueness) with financial data examples, which is helpful when you're actually implementing scorecards or investigating why reconciliation keeps breaking. The regulatory angle is strong, covering what examiners look for and what reporting standards require. Use it when you're building data pipelines that feed compliance, billing, or portfolio systems where bad data creates expensive downstream problems.
npx skills add https://github.com/joellewis/finance_skills --skill data-quality