This skill provides specialized guidance for designing and operating robust data quality management programs within the financial services sector. It covers the six core dimensions of data quality—accuracy, completeness, timeliness, consistency, validity, and uniqueness—while facilitating the implementation of golden source architectures and data lineage for regulatory frameworks like BCBS 239 and MiFID II. It is particularly useful for building validation pipelines for security pricing, client records, and transaction data, ensuring that downstream systems like portfolio management, trading, and compliance operate on trustworthy, audited information.
Key Features
01Golden source architecture and master data management (MDM) patterns
02Validation rule design for security pricing, client, and transaction data
03Data lineage and provenance tracking for BCBS 239 and MiFID II compliance
0418 GitHub stars
05Exception management workflows and data quality scorecards
06Data profiling and anomaly detection for financial data domains
