webinar The Future of Industrial Data Ops: Data Fabric, AI & Manufacturing Industrial data is becoming the foundation for smarter manufacturing, advanced analytics, and AI—but fragmented systems, point-to-point connections, and disconnected data models can make it difficult to turn OT data into meaningful action. In this webinar, Velotic Product Management Leaders, Steve Pavlosky and Abby Eon, explore the future of industrial Data Ops and Velotic’s vision for an industrial data fabric that connects, contextualizes, governs, and activates manufacturing data from the plant floor to the enterprise.Learn how Velotic plans to bring together the strengths of Proficy, Kepware, and ThingWorx to create a unified data foundation designed to simplify industrial data architectures, support real-time and closed-loop operations, and make trusted, contextualized data more accessible to analytics and AI.Watch to learn: Why traditional point-to-point industrial data architectures can limit AI and analytics at scaleHow an industrial data fabric can connect OT data from machines, PLCs, SCADA, MES, historians, and other systemsHow contextualization creates meaning around assets, tags, events, quality, materials, orders, and time-series dataWhy operational and enterprise Data Ops require different approaches to scale and performanceHow Kepware’s connectivity capabilities are evolving to support contextualized industrial dataHow standards including OPC UA, MQTT, Sparkplug B, REST, Kafka, and MCP can improve interoperabilityHow Proficy, Kepware, and ThingWorx can work together through a unified industrial data modelHow trusted, governed industrial data can create a stronger foundation for generative and agentic AIHow a unified data fabric can help manufacturers deploy faster, scale more easily, and reduce data-modeling complexity Fill out the form and watch the webinar to discover how Velotic is building toward a more connected industrial data architecture—where trusted OT data can move from machines and operations to enterprise analytics and AI while maintaining the context needed to drive meaningful action. Welcome BackJohn thomasNot You?Download Resource The Future of Industrial Data Ops: Data Fabric, AI & ManufacturingIndustrial data is becoming the foundation for smarter manufacturing, advanced analytics, and AI—but fragmented systems, point-to-point connections, and disconnected data models can make it difficult to turn OT data into meaningful action. In this webinar, Velotic Product Management Leaders, Steve Pavlosky and Abby Eon, explore the future of industrial Data Ops and Velotic’s vision for an industrial data fabric that connects, contextualizes, governs, and activates manufacturing data from the plant floor to the enterprise.Learn how Velotic plans to bring together the strengths of Proficy, Kepware, and ThingWorx to create a unified data foundation designed to simplify industrial data architectures, support real-time and closed-loop operations, and make trusted, contextualized data more accessible to analytics and AI.Watch to learn:- Why traditional point-to-point industrial data architectures can limit AI and analytics at scale- How an industrial data fabric can connect OT data from machines, PLCs, SCADA, MES, historians, and other systems- How contextualization creates meaning around assets, tags, events, quality, materials, orders, and time-series data- Why operational and enterprise Data Ops require different approaches to scale and performance- How Kepware’s connectivity capabilities are evolving to support contextualized industrial data- How standards including OPC UA, MQTT, Sparkplug B, REST, Kafka, and MCP can improve interoperability- How Proficy, Kepware, and ThingWorx can work together through a unified industrial data model- How trusted, governed industrial data can create a stronger foundation for generative and agentic AI- How a unified data fabric can help manufacturers deploy faster, scale more easily, and reduce data-modeling complexityWatch the webinar to discover how Velotic is building toward a more connected industrial data architecture—where trusted OT data can move from machines and operations to enterprise analytics and AI while maintaining the context needed to drive meaningful action.