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Establishing Sound Data Governance: A Data Catalog Story

Tuesday, June 6, 2023
04:45 PM - 05:30 PM
All Levels

How do you enable thousands of users to intelligently access, use, and understand data? Establishing and maintaining sound governance practices requires more than just the right tools and framework; people must be willing and able to adopt them. 

Hear how Thermo Fisher Scientific was able to successfully sell their data catalog vision internally, implement data intelligent practices, and see immediate value. In this session, you will learn:

  • How corralling your metadata in a data catalog is the essential starting point for governance 
  • How having a user-friendly data catalog is critical for adoption
  • What best practices were implemented to boost catalog adoption 
  • How having a crack support team and built-in educational resources boosted catalog usage and smoothed the path for great governance


John Moran

John Moran

Senior Director, Data Governance Enablement
Thermo Fisher Scientific

John Moran is Senior Director of Data Governance and AI Production at Thermo Fisher Scientific, where he leads initiatives that strengthen data governance, responsible AI adoption, and operational excellence across the organization. He is responsible for establishing governance frameworks, improving data quality, assessing AI readiness, and enabling the use of business context and operational knowledge to deliver trusted, scalable AI solutions with measurable business value.

With close to 30 years of experience in finance, software, and life sciences—including 20 years at Thermo Fisher—John has held leadership roles spanning data governance, master data management, process improvement, and digital transformation. He previously led a global Product Data Management organization responsible for nearly one million products and supported more than 20 acquisitions and portfolio integrations.

John is a frequent speaker on data and AI governance, with a focus on applying governance, context, and human expertise to unlock value beyond large language models.