For much of the past decade, industrial companies have been dutifully collecting data – almost as if it were a badge of honour. More data leads to better decisions – or so the thinking went.
The scale is staggering: nearly 40 billion connected IoT devices are expected by 2030, alongside a global industrial IoT market projected to exceed $1.6 trillion.
Across energy, mining, utilities and manufacturing, organizations invested heavily in connectivity, cloud, data lakes, and digitization programmes designed to aggregate operational information at rapid scale.
Yet many of those initiatives ultimately disappointed because the operational context that gave the data meaning was not preserved. When aggregating information, companies focused on sheer volume rather than quality.
In industrial operations, context is everything. Timestamps, engineering relationships, asset hierarchies, units of measure, and process lineage are the mechanisms through which industrial systems become understandable, trustworthy and actionable.
