From Source to Insight: Data Governance in AI – Workshop With Peter Rawsthorne
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A 90-minute practical guide to building trustworthy AI systems through data provenance, quality, and security – from enterprise solutions to personal AI projects
Join Co. Innovation Centre on February 25th as we host our first workshop with Peter Rawsthorne – From Source to Insight: Data Governance in AI. Join Peter as he provides attendees with a 90-minute practical guide to building trustworthy AI systems through data provenance, quality, and security – from enterprise solutions to personal AI projects. Whether you use AI in a corporate environment or personal projects, this workshop provides practical applications for any instance of AI use.
Date: February 25th, 2025
Time: 9:00am – 10:30am
Location: Co. Innovation Centre
Full workshop description can be found below.
Workshop Description
Description: This 1.5-hour workshop explores the foundational elements of building reliable AI systems through effective data management. Participants will learn how data governance, provenance, lineage, quality, and security work together to create trustworthy AI applications, with practical applications for both corporate environments and personal AI use. The workshop particularly emphasizes these concepts in the context of Retrieval Augmented Generation (RAG) systems, making it relevant for organizations and individuals alike.
Through a combination of instruction and hands-on activities, participants will explore essential practices for managing data throughout its lifecycle. The workshop covers establishing basic data governance frameworks, tracking data origins and transformations, implementing fundamental quality assessment methods, and applying core security measures. Interactive exercises include rapid data source inventorying, basic lineage mapping, and developing simplified governance strategies that participants can immediately apply to their AI projects.
Given the time constraints, the workshop will focus on the most crucial aspects of each topic: basic governance policies and roles, essential provenance documentation methods, fundamental lineage tracking, key quality metrics, and critical security controls. While the 1.5-hour format necessitates a high-level overview rather than deep dives, participants will leave with practical tools and strategies they can begin implementing immediately. The session leverages the facilitator’s real-world experience as a data architect to provide actionable insights and practical examples across various sectors.
About Peter Rawsthorne
Peter is a seasoned technologist with extensive experience in data governance, data quality, data security, technical architecture, and leadership. He excels in designing and implementing robust data management frameworks that support AI-driven initiatives by ensuring data accuracy, security, and compliance. His expertise in architecting secure and compliant data systems aligns with ethical and regulatory standards, laying a strong foundation for AI applications. By integrating data governance principles into AI practices, Peter helps organizations streamline processes, enhance data quality, and maintain compliance with evolving regulations. His leadership skills enable him to guide cross-functional teams in adopting data governance frameworks that support AI innovation, fostering a culture of responsible AI use. This convergence of data governance and AI governance elevates data management and ensures that AI systems operate ethically and effectively, driving business success and competitive advantage.
Find Peter on LinkedIn: https://www.linkedin.com/in/prawsthorne/
