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York's data governance program eyes capabilities, not control
York University has focused its data governance program more on solving data quality, access and trust issues for end users than on controlling their data use.
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Is your data infrastructure ready for the zettabyte era?
AI initiatives are driving demand for curated, controlled data. Leaders must move beyond capacity planning and build the governance and quality practices that make data usable.
Evaluate
The CDO's new role is curating context for data governance
Agentic AI demands that CDOs move beyond cataloging to curating the context AI systems retrieve, creating a new accountability layer for data governance.
News
Nimble launches agents to cull relevant web data for AI
The vendor's Web Search Agents autonomously learn domain-specific use cases to help enterprises collect contextually relevant information for AI and analytics.
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Couchbase evolution continues with new data layer for AI
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Data Management Strategies Evaluate
Is your data infrastructure ready for the zettabyte era?
AI initiatives are driving demand for curated, controlled data. Leaders must move beyond capacity planning and build the governance and quality practices that make data usable.
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Data Integration News
Nimble launches agents to cull relevant web data for AI
The vendor's Web Search Agents autonomously learn domain-specific use cases to help enterprises collect contextually relevant information for AI and analytics.
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Data Governance Manage
York's data governance program eyes capabilities, not control
York University has focused its data governance program more on solving data quality, access and trust issues for end users than on controlling their data use.
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Evaluate
Is your data infrastructure ready for the zettabyte era?
AI initiatives are driving demand for curated, controlled data. Leaders must move beyond capacity planning and build the governance and quality practices that make data usable.
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The CDO's new role is curating context for data governance
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How data mesh supports AI-ready data architectures
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The 5 pillars of data observability
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Problem Solve
York's data governance program eyes capabilities, not control
York University has focused its data governance program more on solving data quality, access and trust issues for end users than on controlling their data use.
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AI doesn't need an unstructured data dump -- move what matters
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8 proactive steps to build trusted data for analytics and AI
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How governance as code controls AI agent risk
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CDO challenges that hinder data-driven initiatives
Chief data officers must turn AI ambition into measurable value. These eight issues show where data strategies break down -- and how leaders can respond.
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AI data fabric emerges as a governance layer for agents
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How agentic AI amplifies data management challenges
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How to use AI to enforce data governance policies
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Data Management/Data Warehousing Basics
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Get Started
How agentic AI amplifies data management challenges
AI agents pose new data management challenges and magnify familiar ones. To build a solid agentic foundation, data leaders must plan for these critical challenges.
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Get Started
Data ontologies are foundational for usable AI outputs
Data ontologies strengthen AI outputs with governed definitions across platforms and departments, helping data leaders boost trust and improve decision-making.
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How to use AI to enforce data governance policies
AI models and agents can automate data governance policy enforcement for proactive governance in dynamic data environments. But don't forget the human element.
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Data integration
Nimble launches agents to cull relevant web data for AI
The vendor's Web Search Agents autonomously learn domain-specific use cases to help enterprises collect contextually relevant information for AI and analytics.
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Data integration
Potential consequences are severe when AI agents lack context
When connected with relevant context, agents can increase organizational efficiency and reduce spending. When left to guess, they can cause significant harm.
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Data management strategies
Data management vendors race to connect AI with context
With agents requiring situational awareness to be accurate, connecting AI with relevant data and business logic has been an almost singular focus throughout 2026.
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