Data can't generate valuable insights and improve decision-making without strong data governance. A data governance maturity model helps organizations evaluate current achievement levels and identify ...

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 ...

Today, Informatica is announcing the launch of Cloud Data Governance and Catalog (CDGC), which unites many prior features of the Informatica platform with new capabilities, all packaged into a ...

AI governance is often treated as a policy problem: define approved uses, create an oversight framework, publish acceptable use rules, and ...

Snowflake is expanding its AI control layer with Dynamic Model Routing as enterprises focus on model costs, governance and ...

The proliferation of AI data, evolving regulatory requirements and risk of large language model (LLM) collapse will help to drive take up of zero trust approaches to data governance in the next two ...

Data’s role as a strategic asset has become increasingly prominent in recent years, chiseled into sharp relief by the numerous organizations using it successfully to respond to rapidly changing market ...

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 ...

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 ...

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

Data governance tends to falter when policies exist, but no one owns the decisions behind them. Large enterprises, faced with increasing regulation and heightened customer and investor scrutiny, have ...