Every organization has elements of data governance somewhere. We’ll share how we built components of data governance and management from the bottom up, where to look for existing components, and how those components now feed into our formal Data Management and Governance Office.

These are just some of the components that were implemented independently by different departments and teams across the technology organization:

• A Data Quality Change Control Board to monitor and resolve issues in market data
• Automated data quality checks and thresholds on data intake, monitored by data operations
• A data advocacy group addressing business data challenges and a cross-business advisory committee managing data assets across the organization
• A homegrown data catalog atop the AWS Data Lake
• An enterprise reference data product
• A central Data Librarian service to answer data questions

These components have become the stepping stones for the larger data management and governance effort at FINRA.

Attendees will learn

• At FINRA, what were the components of data governance at its most atomic level
• How these components functioned and collaborated
• How these components jumpstarted the Data Management and Governance Office
• The path forward for the enterprise Data Management and Governance Office

Speaker: Pragnya Gandhi 

Pragnya Gandhi has over three decades of experience in everything data. She specializes in the architecture and design of complex systems and enterprise data platforms. Today, she supports multiple advanced analytics initiatives as a Senior Principal Architect at FINRA.

Speaker: Lizzie Westin

Lizzie Westin has over 20 years of experience in a variety of data-related roles, including analysis, data integration, content operations, data quality management, program management, and product management. In her current role as Associate Director on FINRA’s Enterprise Data Management team, she oversees third-party data management and facilitates cross-business conversations to create a strategic view of third-party data, coordinate new content opportunities at the enterprise level, and expand knowledge sharing about data and related topics.