Prerequisite: None
David Loshin
President
Knowledge Integrity
David Loshin is an affiliate analyst with TDWI, the author of numerous TDWI research reports, and a frequent featured speaker at TDWI webinars and events. David is president of Knowledge Integrity, Inc. (www.knowledge-integrity.com), and is a recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master data management, and business intelligence. Along with consulting on numerous data management projects over the past 20 years, David is also a prolific author regarding business intelligence best practices; he has written numerous books and papers on data management. David is a frequent invited speaker at conferences, online seminars, and sponsored websites and channels. David is also the program director of the Master of Information Management program at University of Maryland’s College of Information Studies.
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