#data-governance

#data-governance

The leap from chatbot to AI agent is not just about adding automation - it's about architectural transformation, embedding reasoning and action in context.

We heard from our customers and large organizations that managing data access at scale has become a really big problem,

In the past 30 years, advances in data management have been driven by Moore's Law, yet the basic architecture of analytics remains unchanged since 1992.

As I like to say, this path to agentic 'AI heaven' goes through some form of data hell, and that's the grim reality.

We need to move beyond the Babylonian confusion surrounding agents. Some people talk about conversational assistants or chatbots, while others refer to real agentic AI.

During the webinar, attendees will explore concrete methods to identify the hidden costs linked to poor governance of reports, ETL processes, and data usage.

In today's world, where data is power, decentralized architectures like Data Mesh foster innovation by treating data as a product managed by domain teams.

Many firms have no formal data strategy despite increasing AI usage, according to a new study from Carruthers and Jackson.

With the rise in regulatory controls, enterprises now pay more attention to data sovereignty, especially when it comes to data in the cloud, but to know exactly what information they hold is equally important.

Claire Thompson emphasizes that a strategic approach to data governance is essential for innovation, saying, 'I always say data foundations are important for whatever you do next.' A strong data strategy connects regulations to measurable business impacts.

Jules Polonetsky emphasizes that navigating the evolving landscape of data privacy calls for a deep understanding of both policy and technological innovation, making the role of Chief Privacy Officer more critical than ever.