Data Quality

JoelLewis/finance_skills/plugins/data-integration/skills/data-quality

作者 JoelLewis5c498eacf7057e31238c4c5a8012a1afe9ec7c8a無授權條款收錄於 2026年10月9日更新於 2026年10月9日

Design and operate data quality programs for financial data — validation rules, pricing validation, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, detecting stale prices, designing a data quality monitoring framework, calibrating validation thresholds, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, pricing validation, stale prices, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.