The goal of this presentation is to give data governance practitioners a framework to quantify and measure data quality risk. This presentation will cover examples of metrics, discussing concepts, calculations, thresholds, constraints, and visualization techniques in measuring data quality risk. While the presentation covers a detailed framework, practitioners can pick and choose metrics that work for their organizations.

This framework is divided into 3 broad sections

1. Coverage – Does the organization have adequate coverage across various aspects of data quality
   1. Adherence to Enterprise Data Quality Standards.
   2. Data quality risks covered by minimum, registered data quality controls
   3. Critical data elements with detective data quality rule coverage
2. Performance – Do controls perform as expected, and are DQ checks within threshold
   1. Detective Data Quality metrics
   2. Controls design adequacy
   3. Controls operating effectiveness
3. Remediation – Are data quality defects being remediated on time
   1. Share of unresolved defects

The presentation will go into details of each of these metrics with examples of how we have used them, as well as walk through options to create aggregated or weighted scores that incorporate all these metrics into one / few metrics for board-level reporting.

Speaker: Gautam Tamhane, Senior Vice President, Truist Bank

Gautam Tamhane is an experienced data leader spanning various leadership roles in data management and governance in the banking industry, and is currently head of an enterprise-level Data Quality Execution practice for a large bank holding company. 

Speaker: Andrew Bonniwell, Vice President, Truist Bank

Andrew Bonniwell leads the Data Governance metrics and Reporting team, covering metrics and reporting around Data Quality, Metadata, Data Lineage, Data Retention, and Issues management for a 400b+ Bank holding company.