Hype Cycle for Manufacturing Operations Strategy

In this report, Gartner defines Industrial Data Management as the process of contextualizing, normalizing, modeling and transforming data generated in industrial settings. These activities are fundamental to an organization’s ability to collect, store, and use industrial data for initiatives like process performance improvement, scaling IoT use cases, AI implementation, smart manufacturing, and more.  

Gartner views Industrial Data Management as an “Emerging” market with a “Transformational” benefit rating and names HighByte as a Sample Vendor.  

Gartner defines Machine Learning (ML) as an AI discipline that uses statistical models to identify predicted insights and logical patterns based on the analysis of large sets of data. Despite a rising market penetration of 20-50% of the target audience, ML adoption faces obstacles, including data complexity, lack of an industrial data management framework, and heterogenous systems and data sources. The report recommends users ensure the availability, readiness, and context of the data that will be used by ML algorithms to overcome these obstacles.  

Gartner views ML as an “Emerging” market with a “High” benefit rating and names HighByte as a Sample Vendor.