semantic layer

The Enterprise AI Governance Gap Is a Data Problem First

The Enterprise AI Governance Gap Is a Data Problem First

AI, AI Governance, Application Development, Data Management /

Most enterprises are running AI on ungoverned data foundations, and the gap between ambition and operational reality is widening. Quest Software’s Global Field CTO Sue Lane joins ECI Research’s Paul Nashawaty to explain why data quality, semantic layers, and portable governance frameworks determine whether AI investments deliver in production. The governance gap isn’t a maturity problem waiting to close — it’s an active risk posture demanding immediate structural attention.

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Starburst SEIP: A Governed Data Foundation for Enterprise AI

Starburst SEIP is a Governed Data Foundation for Enterprise AI

Agentic AI, Application Development, Data Management /

Starburst has outlined a four-pillar Enterprise Intelligence Platform designed to deliver federated data access, governed semantics, and agentic AI interfaces without requiring data migration. The strategy positions Starburst against hyperscalers by targeting the governed semantic layer as its primary moat. ECI Research analysts examine what the announcement means for enterprise AI readiness and competitive dynamics in the data platform market.

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DataHub Launches AI Context Layer to Fix Enterprise AI Governance

DataHub Launches AI Context Layer to Fix Enterprise AI Governance

AI, AI Governance, Application Development, Data Management, Machine Learning, Software Development /

DataHub is launching a unified context intelligence platform designed to close the gap between enterprise data infrastructure and production-ready AI agents. The release combines automated semantic layer generation, governed context validation, and native SDK integrations for major agentic frameworks. ECI Research sees this as a timely response to an accelerating AI governance deficit across the enterprise.

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