Unified metadata models are emerging as a cornerstone in the changing landscape of data management, highlighting the critical need for integrated frameworks that ensure data accessibility, security ...

To govern AI safely and keep its speed advantage, enterprises must move from static, rule-based control systems to adaptive, ...

About three years ago, Steven Adler was running the privacy consulting practice at IBM. As he talked with IBM customers, he discovered that many of the large customers had some pretty complex IT ...

If you’re reading this, there’s a very good chance your organization’s approach to data governance is the exact opposite of what it should be for the AI era. If you’ve read my prior articles, you know ...

Most data governance models weren’t built for AI. They were designed to ensure compliance, not to support real-time decision-making. They helped manage audits and reports but were never intended to ...

It’s a time when large datasets are being leveraged for real-time analysis. Tried-and-true approaches to cobbling together technologies and policies to achieve workable data governance and security ...

Real-time insights and self-service analytics have become critical for survival in a rapidly evolving data landscape.

A strong data governance foundation is essential for higher education institutions to deploy trustworthy, effective ...

In today’s rapidly evolving digital landscape, the value of data cannot be overstated. Data has become the lifeblood of innovation, driving decisions, shaping industries, and transforming how we live ...

In 2026, it is essential for insurers to have strong data foundations, seamless connectivity, and robust governance to support consistent, fast, and ...

AI and data sovereignty are putting regional data centers at the heart of Europe’s AI evolution. Local data centers and ...

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...