Every organisation investing in security controls, compliance frameworks, and audit processes is operating on an assumption. That the data being protected is understood, complete, and trustworthy. In most organisations, it is not, and the consequences reach far beyond the data team into the parts of the organisation that cannot afford to be wrong.

Data quality is a cybersecurity imperative, and recognising it as one is where more resilient security practice begins. When data assets are misidentified or ungoverned, attackers find the gaps before you do. Incomplete audit trails do not just slow incident response, they make accurate response nearly impossible. Ungoverned data flows grow exposure in ways that even well-designed security architectures were never built to see. Each of these failures shares a common root: cybersecurity and data management treated as independent disciplines, when their interdependencies are precisely where the greatest risk lives. Through the lens of data asset discovery, metadata management, audit log integrity, and data flow governance, this session equips attendees with the technical insight needed to identify and address the points where data quality and cybersecurity intersect most critically.

Attendees will leave with a functional framework for identifying where data quality failures create security risk in their own environments and concrete approaches for closing those gaps without restructuring existing security investments. This session is for anyone who works with, protects, or is responsible for data across any industry, any sector. If you have ever assumed the data beneath your controls is sound, this session is for you.