In this thought-provoking episode of Data Hurdles, hosts Chris Detzel and Michael Burke welcome back Ramon Chen, Chief Product Officer at Acceldata, for an insightful discussion on the rapidly evolving world of enterprise data observability and agentic AI.
Ramon shares how data observability has evolved from an emerging concept to a "full-blown tidal wave" in the industry, now widely recognized as a crucial component of data management that ensures proactive data quality and trustworthiness throughout the data supply chain. The conversation explores how data observability functions as a set of policies and rules that monitor data quality from inception, providing data engineers with timely alerts to resolve issues before they affect business users' reports or downstream AI applications.
The episode dives deep into Acceldata's recent announcement of "Agentic AI data management" - a paradigm shift that applies AI agents to data management in a way similar to their application in customer support and sales. Ramon explains how this approach offers a chat-like interface that adapts to the user's role and intent, providing personalized insights and recommendations about data quality and reliability.
The hosts and Ramon also discuss broader implications of AI advancement, including the changing nature of technical roles, the balance between automation and human oversight, and the emergence of AI observability as a natural extension of data observability. Ramon highlights the upcoming "Autonomous 25" conference on May 20th in San Francisco, where industry leaders will explore agentic AI and its impact on data management.
This episode offers valuable insights for data professionals navigating the intersection of AI and data management in an era of unprecedented technological change.
