The traditional boundaries between operational systems and business intelligence are dissolving. As factories, utilities, and infrastructure generate terabytes of sensor data daily, made accessible through operational technology (OT) systems like Aveva CONNECT, a new paradigm is emerging. One where the convergence of information technology (IT) and OT unlocks unprecedented value through Data Intelligence. With Data Intelligence, everyone from operators to executives can interact with industrial systems through natural language, detect anomalies before they become costly, and plan production based on real-time market data. Organizations mastering this convergence are transitioning to more profitable business models and realizing a lean enterprise.
When OT data from Aveva systems (asset hierarchy, equipment performance, and atmospheric sensors) merges with IT data (market data, resource plans, and supply chain forecasts), a complete operating picture of the value chain becomes visible. This comprehensive perspective enables a repeatable way to infuse AI into business processes and use cases, from root cause analysis and production flow optimization to energy and resource efficiency.
- Data-Driven Competitiveness: Databricks natively integrates with Aveva CONNECT data services, enabling industrial enterprises to access advanced analytics and AI toolchains like AI/BI and the Mosaic AI Agent Framework. This integration democratizes real-time insights into equipment performance, production quality, and operational bottlenecks across the enterprise through natural language and AI agents.
- Scalable Intelligence: The data lakehouse architecture supports scalable, real-time analytics, allowing industrials to monitor and improve key performance indicators, predict maintenance needs, and optimize production processes. This scalable intelligence empowers operations teams to scale their expertise across the organization’s entire operational footprint, comprising millions of sensors and devices.
- Robust governance: Industrials can confidently maximize data value while simultaneously reducing regulatory risks, preventing costly data breaches, and building stakeholder trust, while accelerating data and AI-driven innovation.
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