To optimize success, take a federated approach to your data governance that includes identifying stewards with intention and ...

CEO Sridhar Ramaswamy said enterprise AI is shifting attention away from model benchmarks and toward the quality, governance ...

State and local governments are embracing data modeling and governance strategies to advance efficiency, sharpen decision-making, and elevate their service delivery. In so doing, they’re helping ...

Artificial intelligence is moving rapidly from experimentation into enterprise operations. As organizations focus on increasingly capable models and autonomous ...

AI governance is integral to the core architecture of responsible AI deployments. For enterprises deploying machine learning (ML) or generative AI (GenAI), robust governance is a prerequisite for ...

Gaining control over AI governance starts with understanding how enterprise data is accessed and used. Visibility into the operational data layer lays the foundation for accountability, enabling the ...

Agentic AI brings a new level of urgency to the trust problem and shifts an organization’s risk profile entirely.

Adam Stone writes on technology trends from Annapolis, Md., with a focus on government IT, military and first-responder technologies. State government needs policies and procedures to ensure data is ...

Every month, a manufacturer with multiple plants receives shipment data that is difficult to reconcile. Some plants report net shipped pounds after returns; others report gross shipments and treat ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...