Strategic Focus: Industrial Customer Insights Into AI And Data Management Solutions

Executive Summary

Data management is, visibly or otherwise, already a cornerstone of asset-heavy industrial operations, maintenance and process safety. Industrial data management (IDM) software solutions provide the rigidity and governance facilitating the convergence of information technology (IT), operational technology (OT) and engineering technology (ET) systems to unlock analytics and AI-driven use cases. This report examines the realities of IDM solutions as viewed by its practitioners, discussing trends such as unified namespace (UNS) architectures, industrial DataOps and platform partnerships that provide industrial-grade scalability and deliver actual value. The report also highlights where challenges – such as data quality issues, cybersecurity hurdles and vendor lock-in – persist. We outline best practices for successful IDM deployment, such as gradual implementation, standardization of data models and historicizing time series data. Industrial Internet of Things (IIoT), data transformation leaders and analytics practitioners should use these insights to build resilient, scalable IDM platforms foundational to modern-day operational excellence.