Overcoming Data Management Challenges for AI Success
Webinar Speaker: Evan Levy, TDWI Research Fellow
Date: Tuesday, September 23, 2025
Time: 12:00 p.m. PT / 3:00 p.m. ET
As organizations race to implement artificial intelligence initiatives, they face an increasingly complex data landscape that threatens to undermine their AI success. The exponential growth of data sources creates significant challenges in data quality, governance, and accessibility.
Modern AI projects demand clean, well-governed, and readily available data, yet many enterprises struggle with data silos, inconsistent formats, and lengthy preparation cycles that can delay AI model development. Without robust data management foundations, even the most sophisticated machine learning algorithms fail to deliver meaningful business value.
In this webinar, we’ll explore how a modern approach to data management is essential for enabling responsible and scalable AI initiatives. Join TDWI research fellow Evan Levy and experts from Microsoft and Informatica to hear how these two companies work with their clients to eliminate data silos, streamline data pipelines, and ensure that high-quality, trusted data is always available for analytics and machine learning workloads. Hear real-world examples of how enterprises are improving productivity, increasing data confidence, and driving smarter business outcomes through AI.
Discussion topics include :
- The relationship between agentic AI, generative AI, and a modern data management approach
- The evolution (and importance) of enterprise-class data services (discovery, ingestion, data trust/quality, integration, governance) within the AI development life cycle
- The challenges that exist in delivering AI solutions with trusted, high-quality data
- The competing priorities of security and accessibility when building AI solutions that require both on-premises and cloud data sources
Evan Levy, CBIP