What Is a Data Historian?
A data historian is software built specifically to collect, store and retrieve time-series data from industrial operations: sensor readings, equipment states, alarms and other values coming off PLCs, SCADA systems and control networks. It keeps a time-stamped record of what happened on every machine and process, so teams can see current performance, look back at past events and spot patterns over time. Data historians are used widely in manufacturing, and in industries with distributed assets such as wind farms.
Why operational data is so hard to keep without a historian
Machines and control systems generate a constant stream of readings, often every second. Without a system designed to capture it, that data is overwritten, stays locked in individual controllers or gets exported by hand into spreadsheets, so the history needed to understand performance simply isn't there when you need it.
That leaves operations teams working without the full picture:
- Readings from PLCs and SCADA systems lost or overwritten before anyone can use them
- No reliable record of what happened before a breakdown, alarm or quality issue
- Operational data trapped in individual machines, lines and sites
- Time-series data too large and fast-moving for spreadsheets or standard business databases
How a data historian actually works
- 01
Connect to the control layer
The historian connects to PLCs, SCADA systems and other control networks, collecting readings directly from equipment.
- 02
Capture time-series data continuously
Every sensor reading, equipment state and alarm is recorded with an accurate timestamp, as it happens.
- 03
Store it efficiently at scale
Historians are built to compress and store years of high-frequency data, far more than a standard database handles well.
- 04
Retrieve and analyse it quickly
Teams can pull up current values or look back at any point in time to investigate events, compare shifts and spot trends.
- 05
Feed it into the wider business
Historian data flows into dashboards, reporting, a Unified Namespace and analytics, so operational data sits alongside business data.
What this means in practice
- A complete, time-stamped record of every machine and process
- Faster root-cause analysis when something goes wrong
- The history needed for predictive maintenance and OEE tracking
- Operational data from multiple sites and assets in one place
- A reliable source of shop floor data for reporting and AI
Inpute works with leading data historian platforms, including AVEVA PI, Canary and Ignition, to capture, store and structure time-series data from industrial operations, and connect it to the reporting and analytics teams rely on.
How Inpute helps organisations get value from a data historian
We help you choose, implement and connect the right data historian for your operation, working with AVEVA PI, Canary and Ignition, matched to your equipment, your sites and the systems you already run.
A historian is most valuable when its data doesn't stay on the shop floor. We connect historian data to your wider data infrastructure, so it feeds live dashboards, maintenance planning and business reporting.
Where this fits with the rest of your data strategy
A data historian is often the first step in turning machine data into live insights. It is also a key source for a Unified Namespace, and a foundation for Real-Time Intelligence use cases such as improving OEE.
Frequently asked questions
A data historian is software that collects, stores and retrieves time-series data from industrial operations, such as sensor readings, equipment states and alarms from PLCs, SCADA systems and control networks.
Historians are designed for time-series data: high volumes of time-stamped readings arriving continuously. They store it efficiently, keep years of history and retrieve it quickly by time, which standard business databases aren't built to do.
Mainly manufacturing and process industries, but also any business with distributed industrial assets, such as wind farms, where readings need to be collected from many locations.
No. A Unified Namespace gives operational data one consistent, real-time structure, while a historian keeps the long-term record of that data. The two often work together.
Data Infrastructure use cases we deliver
Data infrastructure is the foundation everything else runs on. Clean, connected and governed data is what makes automation, AI and real-time reporting work.
- What Is a Scalable Data Infrastructure?
What a data foundation needs to look like to support growth, automation and AI.
- What Is a Data Historian?
Capture, store and retrieve time-series data from machines, sensors and control systems.
- How Do Organisations Fix Data Quality Issues at the Source?
Find and fix the errors that make people distrust the numbers.
- How Do Manufacturers Turn Machine Data into Live Insights?
Capture machine data, cleanse it and turn it into real-time operational insight.
- What Is a Unified Namespace (UNS) and Why Do Manufacturers Need One?
One consistent structure for operational data across sites, lines and systems.
- Why Is Clean Data a Prerequisite for Reliable AI?
Why AI is only as good as the data behind it, and what to fix first.
See how this would work for your operation
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