Absent a comprehensive federal AI framework, agencies should be guided by four governance priorities. While the federal ...

A phased guide to AI governance in cloud-native systems, aligning ISO 42001:2023 and NIST AI-RMF with lifecycle controls, ...

The ongoing dive into modernity—and all the new technologies and hype trains that come along with it—requires a modern data architecture to support it. With this architecture comes a variety of other ...

Data governance is transforming the world of business and IT as organizations increasingly acknowledge and embrace the importance of data in the modern world. And this transformation significantly ...

In the ever-evolving landscape of data management and utilization, it's crucial to address the prevailing myth that data governance and master data management (MDM) are disciplines strictly reserved ...

India's AI framework proposes a layered, lifecycle approach. But how will it work in practice, and what challenges does it ...

Data fabric is a powerful architectural approach for integrating and managing data across diverse sources and platforms. As enterprises navigate increasingly complex data environments, the need for ...

Dataiku’s field chief data officer for Asia-Pacific and Japan discusses how implementing AI governance can accelerate ...

The field of data and analytics is rapidly growing and evolving, requiring creativity, skill and a deep understanding of emerging technologies, particularly in data governance. Advanced strategies for ...

CU Boulder collects, uses and maintains a significant amount of data. This includes, but is not limited to student, employee, research and finance data. Institutional data supports CU Boulder’s ...

In 2025, enterprises are leveraging AI capabilities to enhance data management. Just like 2023, 2024 was a dynamic year for enterprise data management, and 2025 is shaping up to bring even more change ...