Prerequisite: None
This session will include a moderated Q&A featuring questions from the live audience.
Artificial intelligence (AI) and business intelligence (BI) promise faster insights and better decision-making to support the modern data-driven enterprise. The idea of self-service BI and analytics solutions that allow businesspeople to drive their own reporting and visualizations is enticing. Yet many organizations struggle with successful self-service due to unclear data definitions, manual processes, and overly technical interfaces and data sets. In this session, Donna Burbank will outline a modern approach that combines data automation with a universal semantic layer to bridge these gaps and create a trusted foundation for analytics and AI. A semantic layer provides a “business-friendly” interface for business stakeholders that can help support user-friendly self-service.
Attendees will learn how a universal semantic layer and automation work together to standardize business logic, streamline data pipelines, and make governed data accessible across tools and users. By centralizing definitions for metrics, dimensions, and relationships, organizations can ensure that AI models, BI dashboards, and self-service queries all operate from the same trusted data context—reducing duplication, improving consistency, and accelerating time to insight. The session will conclude with a live audience Q&A, giving participants the opportunity to ask questions about architecture, tools, governance strategies, and real-world adoption.