Industrial Data, Historian, IIoT and AI Readiness
Use this hub to turn raw equipment signals into governed, contextualized, inspection-ready data that can support dashboards, PAT, predictive maintenance, and AI use cases.
Who this helps
IT/OT, data, engineering, and quality teams building trusted process data foundations for analytics and AI.
Authority proof
Connects historian and data lake decisions to ALCOA+, validation, cybersecurity, and operations ownership. Prioritizes trusted data foundations before advanced AI claims. Shows where edge, IIoT, OPC UA, PAT, and digital twins fit inside a regulated architecture.
Reading path
Start with Pharma Data Lake Architecture, then use the supporting articles to validate decisions, risks, owners and implementation sequence.
How to use this page
Use this Industrial Data, Historian, IIoT and AI Readiness page as a planning checkpoint before vendor selection, architecture review, validation scoping or implementation sequencing. The strongest next step is to compare the guidance with your current SOPs, system inventory, batch records, data flows and QA review routines so the discussion starts from evidence instead of assumptions.
Evidence to prepare
For Industrial Data, Historian, IIoT and AI Readiness, prepare the records, owners, risks and decision criteria linked to who this helps, authority proof, reading path. Useful evidence includes current process maps, interface lists, audit trail expectations, exception workflows, data retention rules and the business reason for changing the current operating model.