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presented by KeyMark
Summary
Data lakes remain sources of truth, but AI accesses data beyond what lives in a lake to acquire valuable metadata and semantic understanding.
In this episode of the Mostly Unstructured Podcast, KeyMark CMO Clay Tuten sits down with Josh Heller of Crushable.ai, to dismantle the myth that a lake has to be the final resting place of data.
Read the companion article for info on data at rest vs data in motion, and integration tactics: https://www.keymarkinc.com/have-the-best-practices-for-data-integration-changed/
TOPICS COVERED IN THIS EPISODE:
• What separates a data warehouse from a data lake?
• Why the semantic layer is the most underrated shift in enterprise AI right now?
• How AI vectorizes unstructured data — and why that changes the data-readiness conversation?
• The difference between access and storage and which matters more?
• How do “conversational data queries” replace legacy BI dashboards across every level of an org?
QUESTIONS THIS EPISODE ANSWERS:
• Is a data lake still necessary for enterprise AI?
• How do you operationalize data not in a lake?
• What is a semantic layer?
• How do you know when your data foundation is good enough to move forward with AI?
• What should enterprise leaders audit before starting an AI initiative?
• Why does agentic AI make data governance more important?
WHO THIS IS FOR:
CDOs, CIOs, and operations leaders looking to understand if they should double down on data lakes, or embrace MCP connectors. And, anyone evaluating enterprise AI, intelligent automation, or agentic AI during a fundamental shift in the understanding of data access.
Subscribe to the Mostly Unstructured Podcast for more conversations on enterprise AI, data readiness, and intelligent automation from the team at KeyMark.
