The Missing Layer for Trusted AI: Why Metrics Need Meaning
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(00:00:00) The Missing Layer for Trusted AI: Why Metrics Need Meaning (00:00:01) Why Inconsistent Metrics Are an AI Risk (00:02:35) Why the Same KPI Produces Different Numbers (00:05:37) The Business Context Behind Every Metric (00:07:48) Why Metrics Need a Governed Semantic Layer (00:11:21) How Metric Governance Makes AI More Trustworthy (00:17:12) The Big Takeaway: From Data Access to Trusted Context In this episode of AI Data Bites (Powered by Denodo), host Neha Gurudatt sits down with Kevin Bohan, Director of Product Marketing at Denodo, to explore how inconsistent metrics can undermine trust in analytics and AI - and how governed Metric Views can help. Topics Covered: Why different teams can get different answers from the same KPI How metrics capture business logic - not just calculations Why governed metrics matter for AI accuracy and trust How Metric Views create reusable, consistent business context Why This Episode Matters As AI takes on a bigger role in business decision-making, trusted data needs trusted business meaning. Metric Views help provide the consistent context analytics and AI systems need to deliver reliable answers.
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