Prerequisite: None
Astonishing growth in agentic AI, generative AI, machine learning, and AI-infused applications is putting tremendous pressure on data delivery. Unfortunately, data delivery is often constrained by legacy data architectures built to serve traditional requirements and by data fragmentation across disconnected silos and tiers.
AI democratization is changing data demands as business leaders across enterprises seek to innovate with AI in how they manage operations, optimize processes, evaluate financial and market performance, and engage with customers. Demand for greater data diversity, speed, and volume driven by AI development and operationalization is only increasing.
TDWI research fellow David Stodder will discuss how organizations are responding to these pressures to modernize data delivery. Stodder will highlight technology trends and directions for achieving AI readiness with modern data delivery and examine the latest TDWI research to identify best practices for successful AI readiness.
Stodder will then lead a panel of experts to discuss practices for successful data delivery in the modern era of AI.
Key issues to be covered include:
- How data platforms and pipelines are evolving to increase AI readiness for data delivery and to enhance AI development and operationalization
- The importance of semantic layers and data intelligence technologies such as catalogs to achieving AI-ready data delivery
- The vital role of observability for governance, quality, and troubleshooting data