GenAI is transforming industries, but as it evolves, it requires a robust governance, risk and compliance strategy.

From the Human Genome Project to large-scale initiatives like the UK Biobank and The Cancer Genome Atlas (TCGA), the recent ...

In a centralized governance framework, different data is categorized differently, with certain governance levels requiring, for example, additional metadata fields or a certain level of service.

Too many data-governance efforts are focused simply on using data to measure compliance, Stefaan G. Verhulst writes.

Data governance impacts both internal and external audiences. Viewing data as an enterprise – not individual – asset is the first step towards a strong program.

Enterprise data platforms increasingly unite analytics, governance and orchestration, with new generative and agentic AI-enabled features to improve autonomy and speed.

Generative AI introduces new risks, challenges, and opportunities for how organizations source and use data. Here are four ways data governance teams are rising to the occasion.

Data governance is required in order to protect personal data and to ensure that ethics are upheld. This may sound straightforward but it comes at a time when public trust in how ‘big business ...