Data Historian
Building Your AI-Native Industrial Data Foundation
The data foundation you build today will determine what is possible tomorrow. It is the one asset that persists, accumulates value, and supports every layer built on top of it.
Jeff Tao
April 12, 2026 | AI-Native Industrial Data Foundation, Data Historian
The Future of Industrial Software: AI Agents on Top of an Industrial Data Foundation
Applications are no longer long-lived assets, but flexible and disposable layers on top of something more fundamental.
Jeff Tao
April 11, 2026 | AI-Native Industrial Data Foundation, Data Historian
Total Cost of Ownership: The Hidden Cost of Industrial Data Systems
The total cost of an industrial data system is not defined by its license or subscription price. It is defined by its complexity, its integration effort, and the people required to make it work.
Jeff Tao
April 10, 2026 | AI-Native Industrial Data Foundation, Data Historian
Why Industrial Data Must Be Open — Without Losing Context
If industrial data platforms are not open, every new AI capability requires custom integration, making it difficult to keep up with the pace of innovation.
Jeff Tao
April 8, 2026 | AI-Native Industrial Data Foundation, Data Historian
AI-Driven Operational Insights: Removing the Barrier Between Data and Understanding
AI-driven operational insights remove the barrier to understanding data by making it possible to generate insights without requiring deep expertise in analytics or domain modeling.
Jeff Tao
April 7, 2026 | AI-Native Industrial Data Foundation, Data Historian
Asset-Centric and Event-Centric Visualization: From Dashboards to Operational Understanding
What industrial users need is a new kind of visualization—one that is asset-centric, event-aware, insight-driven, and tightly integrated with the data foundation.
Jeff Tao
April 2, 2026 | AI-Native Industrial Data Foundation, Data Historian
Advanced Analytics in Industrial Systems: Beyond the Historian
Organizations increasingly expect systems to generate insights—detect anomalies, predict future behavior, identify patterns, explain deviations and analyze the root cause.
Jeff Tao
April 2, 2026 | AI-Native Industrial Data Foundation, Data Historian
Event-Centric + Asset-Centric: The Missing Link in Industrial Data
Assets define what exists. Events define what happens. Only when both are modeled together can we truly understand industrial operations—and only then can AI become genuinely useful.
Jeff Tao
March 30, 2026 | AI-Native Industrial Data Foundation, Data Historian
How AI Helps Engineers Move from OEE Monitoring to Root-Cause Analysis
A low OEE number by itself is not very useful. What matters is whether the loss is coming from uptime, speed, or quality, and whether the team can isolate the cause quickly enough to act.
Jim Fan
March 29, 2026 | Data Historian, Industrial Data
Why Time-Series Data Alone Is Not Enough: Rethinking Industrial Event Analysis in the Age of AI
To fully realize the value of industrial data, events need to become a native part of the data foundation, not an optional layer.
Jeff Tao
March 26, 2026 | AI-Native Industrial Data Foundation, Data Historian
