The goal of data governance is to ensure your organization’s data is business-ready: high-quality, accessible, secure, and ...

To get the most out of empowering business technologists, organizations need to promote projects heavily while managing them tightly.

Unlock the power of your data with an effective data governance framework for security, compliance, and decision-making. Data governance frameworks are structured approaches to managing and ...

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

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.

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

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

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

Data governance controls all elements of company data, including how it's managed, mined, analyzed, protected, gathered, and stored.

Optimal data governance has several potential impacts on maintaining and continually improving an organization's customer experience.

Is it better to monitor for quality or detect problems? It depends. Here's how to choose between active and passive data governance.

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.