A Graph for All Your Data? And AI?

The forcing function of AI and agents puts tremendous pressure on data teams to get their house in order. The demands for getting "AI-Ready" are coming from all sides, and there are countless methods being touted. The most promising approach? A graph for all your data! Internet powerhouses like Meta, LinkedIn and others have demonstrated the remarkable power of graph technology. Join this episode of InsideAnalysis to learn how your organization can connect all the dots, and enter the AI era with confidence. Harsha Chintatalapani of the OpenMetadata Project, and Co-Founder of Collate, will demonstrate how semantics can be baked into every data structure via automation and curation using open standards. Also joining the show will be world-renowned Data Maven, Jessica Talisman, who will explain how a data graph can solve for the many challenges that Master Data Management and Data Virtualization were supposed to fix. She'll also share how Web Ontologies (OWL) and Reference Description Frameworks (RDF) are finally coming into their own, offering tremendous promise for enabling the semantics that can pave a smooth transition into Enterprise AI. What you'll learn: • The difference between a data graph and a domain ontology, and why it matters for AI • How semantic metadata graphs connect your domain logic to enterprise data assets • What OWL and RDF enable that data catalogs and MDM tools cannot • How to get started quickly using RDF/DCAT standards, automated semantics, and glossary-to-source linking