For decades, data governance in regulated financial institutions has rested on a familiar foundation. Policies are documented ...

Organisations are beginning to implement zero-trust models for data governance thanks to the proliferation of poor quality AI ...

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 ...

I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

Without high-quality, well-governed data, every downstream AI initiative becomes fragile, expensive, inaccurate or downright ...

Gartner predicts that by 2028, 50% of organizations will have had to adopt a zero-trust posture for data governance as a ...

Optimal data governance has several potential impacts on maintaining and continually improving an organization's customer experience. Data is the lifeblood of an organization. Customers and employees ...

The COVID crisis has shown that ethical and effective uses of data and increased sharing of data can save lives and can be critical for society as a whole (by contrast to the use of data made by ...

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’ uses ...

A blended approach combines centralized policy compliance with decentralized flexibility. In association withCapital One Data governance has historically been a serious bottleneck for analytics. While ...

Why is data literacy important to data governance? Your email has been sent Data literacy is a key component of data governance. Learn why it’s important to data ...