Process industries generate staggering volumes of operational data from thousands of sensors, instruments, and control systems. The irony is that despite this data richness, most organisations still rely on manual analysis and monthly reports to make operational decisions.
Building the Data Foundation
Before sophisticated analytics is possible, the data foundation must be in place. This means reliable collection from process historians, proper data governance to ensure quality and lineage, and a unified data platform that makes data accessible to both engineers and data scientists.
From Descriptive to Prescriptive Analytics
- Descriptive: What happened? (dashboards, reports, KPI monitoring)
- Diagnostic: Why did it happen? (root cause analysis, drill-down)
- Predictive: What will happen? (ML forecasting, anomaly detection)
- Prescriptive: What should we do? (automated recommendations, closed-loop control)
