New & Notable
Evaluate
Why anonymization alone no longer protects sensitive data
Anonymized data is still valuable, but organizations that rely on it alone can expose their business and customers to privacy, regulatory and reputational risk.
AI doesn't have a trust problem. Your data does.
The AI auditability gap isn't an AI problem. It's decades of data management debt, finally coming due, exposed by autonomous decision-making.
News
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.
Manage
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.
Topics Covered
Find Solutions For Your Project
-
Evaluate
Why anonymization alone no longer protects sensitive data
Anonymized data is still valuable, but organizations that rely on it alone can expose their business and customers to privacy, regulatory and reputational risk.
-
Why more data will not deliver AI data readiness
-
AI pressures expose outdated data pipeline architecture
-
Five pressures that break AI programs after the pilot
-
-
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.
-
York's data governance program eyes capabilities, not control
-
AI doesn't need an unstructured data dump -- move what matters
-
8 proactive steps to build trusted data for analytics and AI
-
-
Manage
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.
-
How CDOs can show the business impact of data
-
What AI-native analytics startups offer that BI vendors don't
-
Modern IT threats demand continuous resilience
-
Data Technologies Basics
-
Get Started
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.
-
Get Started
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.
-
Get Started
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.
Multimedia
-
-
Get Started
Enterprise backup as a service explained
-
-
News
View All -
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.
-
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.
-
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)?