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Integrate structured and unstructured data for better AI outputs
For AI agents to give the most accurate, informed responses, organizations must provide them with all the facts. Even those that are hidden in an old email or customer claim.
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.
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.
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.
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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 to get reliable BI insights from AI-augmented analytics
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How data mesh supports AI-ready data architectures
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Problem Solve
AI value comes from continuous learning, not automation
The companies pulling ahead in AI aren't doing it by deploying more tools. Rather, they're building the data foundations that make intelligence reusable, scalable and reliable.
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York's data governance program eyes capabilities, not control
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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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Manage
Modern IT threats demand continuous resilience
Continuous resilience enables organizations to anticipate, withstand and recover from disruption. Modernize today to reduce operational risk and improve business agility.
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CDO challenges that hinder data-driven initiatives
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Your AI isn't failing -- your metrics are
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AI data fabric emerges as a governance layer for agents
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Data Technologies Basics
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Integrate structured and unstructured data for better AI outputs
For AI agents to give the most accurate, informed responses, organizations must provide them with all the facts. Even those that are hidden in an old email or customer claim.
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Business resilience vs. business continuity: Key differences
Business continuity and resilience go hand in hand and play a role in an organization's disaster recovery plan. Essentially, business continuity is needed to achieve resilience.
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How to get reliable BI insights from AI-augmented analytics
Before adopting AI-powered BI applications, organizations need stronger business context, trusted workflows and users prepared to assess AI outputs.
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Enterprise backup as a service explained
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News
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Data Management
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 Management
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
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.
Data Technologies Definitions
- What is data visualization?
- What is customer data integration (CDI)?
- What is data restoration?
- What is data analytics (DA)?
- What is a backup storage device?
- What is off-site backup?
- What is an entity relationship diagram (ERD)?
- What is data as a service (DaaS)?