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AWS emphasizing database security as AI powers new threats
While the tech giant has always focused intently on protecting proprietary data, its database security capabilities are taking on new importance as agents increase vulnerabilities.
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Data contracts gain urgency as AI tests data foundations
Unreliable data can undercut AI efforts before they deliver meaningful returns. Data contracts help clarify accountability and move quality controls upstream.
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How CDOs can show the business impact of data
CDOs can defend the spend on data programs by tying outcomes to saved time, lower risk, revenue gains and AI projects that reach production.
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Data observability specialist Bigeye puts focus on AI spend
With agentic AI costing more than many organizations expected, the data observability specialist's latest alerts users when the expense of an agent suddenly changes.
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Why more data will not deliver AI data readiness
Volume-first data strategy served the BI era but falls short for agentic AI, where the constraint on readiness is context and governance rather than how much data exists.
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AI pressures expose outdated data pipeline architecture
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Five pressures that break AI programs after the pilot
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7 expert recommended data observability tools
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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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Data contracts gain urgency as AI tests data foundations
Unreliable data can undercut AI efforts before they deliver meaningful returns. Data contracts help clarify accountability and move quality controls upstream.
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How CDOs can show the business impact of data
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What AI-native analytics startups offer that BI vendors don't
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Modern IT threats demand continuous resilience
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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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Data Management
Data observability specialist Bigeye puts focus on AI spend
With agentic AI costing more than many organizations expected, the data observability specialist's latest alerts users when the expense of an agent suddenly changes.
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Data Management
Snowflake targets cost of AI with dynamic model routing
With spending on AI spiraling out of control for many organizations, the vendor's latest new feature automates model selection to balance cost and performance.
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Data Management
IPO inevitable for Databricks after adding $5B in funding
Experts note that the benefits of going public ultimately outweigh those of staying private, even with the vendor seemingly able to raise unlimited financing.
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)?