Data Quality

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

by JoelLewis5c498eacf7057e31238c4c5a8012a1afe9ec7c8aNo licenseListed Oct 9, 2026Updated Oct 9, 2026

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.

  1. 5c498eacf7057e31238c4c5a8012a1afe9ec7c8aCurrentcommit 5c498eaPublished Oct 9, 2026

Source and attribution

Source:JoelLewis/finance_skillsinplugins/data-integration/skills/data-qualityat commit5c498ea

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal