Webinar: The Optimal AI Architecture: How a Data Hub, Data Quality, and a Data Catalog Can Make All the Difference

Artificial intelligence is on every agenda. But in practice, many AI projects fail not because of the technology—but because of a lack of data. Data is scattered, inconsistent, incomplete, or simply undocumented. The result: AI pilots that can’t scale. Models that no one trusts. And investments that don’t deliver the expected results.

So what does it take for AI to really deliver?

We've got the answers! In this free webinar, we'll show you why data quality, a data hub, and a data catalog aren't just side projects—they're the essential building blocks for scalable, effective AI. And we'll explain how companies can take a practical approach to establishing this foundation.

Highlights:

• Why AI Initiatives Fail: Common Mistakes and Obstacles—and What Really Needs to Be Addressed First
• Understanding the Data Hub: How Companies Make Data from Various Sources Centrally Available and Usable
• Data Quality as an Ongoing Task: Why Poor Data Leads to Poor Models—and How to Systematically Ensure Quality
• The data catalog as an enabler: How transparency regarding data assets fosters trust, governance, and collaboration
• From theory to practice: A pragmatic maturity model – from “understanding data” to “building AI effectively”

This webinar is for you if…

• You are planning or have already launched AI initiatives—and are struggling with AI architecture
• As a CDO, AI lead, or data specialist, you want to lay a solid foundation for AI
• You want to know where to start in a practical way—without waiting for perfect conditions