04/22/2024 | News release | Distributed by Public on 04/22/2024 03:50
Most industrial firms have data sources - and plenty of them. This often comprises high volumes of timestamped measurements being gathered from IoT sensors every second, or values recorded by operators with hand-held devices once a month for the last decade, as well as maintenance records stored in EAM/CMMS. However, unlike most enterprise data, which can usually be stored in neat tables, industrial data also entail digital and handwritten technical documents, engineering drawings, inspection reports, audio recordings, images, streaming CCTV data and 3D models of assets. The challenge is no longer gathering operational data but rather being able to make sense of it.
Industrial AI analytics software takes on this challenge by leveraging machine learning (ML) models to analyse vast arrays of IT and OT data to predict failures, prescribe maintenance actions, optimize production, improve energy management and reduce emissions. As such, the industrial AI analytics software market is flourishing, with Verdantix forecasting that spend will grow at a CAGR of 23.9% and will reach $5 billion in 2028. However, the insights from AI and ML models are only as good as the data coming in. Hence, data quality, availability and contextualization become critical to enable successful AI deployments, including generative AI (GenAI).
When searching for a data management solution to unify data across their industrial operations and produce accurate, valuable and timely insights, buyers should focus on vendors who offer:
To learn more about the key providers of industrial data management solutions and what criteria you should consider before choosing a provider, read the recently published Verdantix Buyer's Guide: Industrial Data Management Solutions (2024) report by signing up to Verdantix Vantage.
Sayanh is an Analyst in the Verdantix Operational Excellence practice. Prior to joining Verdantix, she completed an MSc in Chemistry with Molecular Physics at Imperial College London. Here, she undertook research in renewable energy, focusing on improving the thermal stability of organic solar cells under manufacturing and operating conditions.