In this episode, we explore a simple but often overlooked idea: manufacturing AI only works when the data is ready for it. Before models, predictions, or chat interfaces, there needs to be structure, context, and reliable data flow. The discussion looks at how a Unified Namespace (UNS) and Sparkplug B help create that foundation by organizing machine data, maintaining state, and keeping systems aligned. We talk about why many AI experiments struggle when the underlying data architecture is messy, and how clear data structure can make advanced analytics far easier to build and maintain. It’s a calm, practical conversation about preparing factories for AI the right way — starting with the data layer. For deeper reading and more real-world insights, visit iiotblog.com.