Level: Beginner to Intermediate
Prerequisite: None
Data privacy laws such as GDPR and CCPA have raised organizational awareness about the need for governance practices to prevent exposure of individual personal and private data. Yet the scope of ensuring against the inappropriate use of information truly extends way beyond the processes for data protection, especially as the accelerating corporate adoption of generative AI and large language models opens the door for reliance on faulty and biased AI-based applications.
Information risk is the potential for any organizational loss of value due to issues associated with ungoverned management of information. These issues encompass a variety of undesirable outcomes, ranging from missed business opportunities, unauthorized use of sensitive information, penalties assessed for regulatory noncompliance, negative public opinion, integrated bias in AI systems, and ultimately adverse business decision-making. This course will define information risk and provide a framework for defining, categorizing, and mitigating the vulnerabilities that lead to potential adverse effects. The instructor will frame aspects of data policies to operationalize risk assessment, identification of vulnerabilities, and ways to establish controls to monitor and assess information risks.
You Will Learn
- How to improve overall data utility
- Classification of data resources in relation to data policy directives
- How to establish guardrails to protect against exposure of sensitive data
- How to draft records management policies for data retention
- How to catalog data resources to improve accessibility
- How to develop guidelines for ethical and appropriate data use for AI
Geared To
- Data governance practitioners
- Data privacy practitioners
- Data analysts
- Policy and compliance managers
- Data and analytics program managers