ML-Generated Metadata and Agile Governance: Transforming Data Trust and Accessibility in Oil & Gas

As digital transformation accelerates across the oil and gas value chain, the importance of trustworthy, accessible, and contextual data is greater than ever. In this insightful session, Jason Baihly and Raj Kannan of SLB will shed light on how ML-generated metadata and Agile Data Governance are revolutionizing how energy companies handle their most critical data assets. 

The session will tackle real-world challenges—like manual data cataloging, version confusion, and storage bloat due to duplicated files—and how these pain points hinder operational efficiency and compliance. A local case study will highlight the profound impact of poor data organization on data science initiatives, revealing how ineffective systems can lead to unreliable, duplicated, and inconsistent datasets. 

Jason and Raj will demonstrate how a scalable, cloud-based metadata management system, coupled with agile and intuitive governance, can shift data management from a burden to a value driver. These solutions enable better regulatory reporting, enhance team collaboration, and accelerate digital transformation, particularly for companies navigating complex asset acquisitions.