Prerequisite: None
As enterprises strive to fully harness the potential of AI, creating a modern data ecosystem that facilitates AI-driven transformation is crucial. In this session, we will examine what a data architecture designed for AI looks like and how it can enhance an organization’s capacity to support its data innovation journey. This session will offer a blueprint and case studies on integrating ERP data with other enterprise data sources, demonstrating how a cohesive data ecosystem equips AI models with the context and flexibility necessary for complex analysis and predictive capabilities.
Attendees will hear how enterprises have leveraged modern data architectures, supported by scalable data storage, cloud integrations, and real-time processing, to provide a foundation for effective AI. We will discuss best practices for unifying ERP, customer, and operational data to create a central and reliable source of truth, which AI models can utilize to deliver actionable insights. We will present strategies for building adaptive data pipelines, leveraging data lakes, and using knowledge graphs to ensure that data remains accessible, accurate, secured, and optimally structured for both AI and analytics applications.
Designed for data leaders and IT professionals, this session provides a roadmap for building a data platform that supports and drives your data innovation journey. By blending technical strategies with a focus on pragmatic implementation, this presentation will help organizations position their data architecture to harness AI and make an impactful difference in today’s competitive landscape.