Prerequisite: None
This session will include a moderated Q&A featuring questions from the live audience.
As organizations accelerate their AI initiatives and advanced analytics programs, enterprise data management is experiencing a shift in how capabilities are delivered and consumed. This presentation examines the key trends reshaping data management practices and the evolution of capabilities required to operationalize enterprise data at scale while maintaining trust, quality, and governance for analytics and AI workloads.
TDWI research fellow Evan Levy will discuss how foundational data management disciplines—including master data management, data quality, metadata management, and data governance—are being reimagined to support both traditional analytics and machine learning applications.
This session will examine how modernizing the data stack empowers data management capabilities that accelerate analytics and AI initiatives. Attendees will gain practical insights into trends that balance agility with control, enabling self-service access for data scientists, analysts, and users while maintaining enterprise-grade governance that ensures all systems operate on a trusted data foundation.
Join Evan Levy to discover how leading companies are modernizing their data stacks to ensure that high-quality, trusted data is accessible and available for analytics and machine learning workloads.