Smart Innovators: Industrial Data Management Solutions

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Executive Summary

Data represents reality, but is not reality itself. It consists of symbols and numbers used to convey information, but is not the information itself. As a human-made construct, data is often manipulated and transformed to serve a specific purpose, which can compromise its authenticity or accuracy. Without proper processes in place to manage access, track transformations and provide context to human operators, the unstoppable universal truth of increasing entropy will begin to introduce bias and error into the data, further distorting its representation of reality. To aid customers in navigating the complex and rapidly evolving field of industrial data management, this report examines the capabilities of 20 vendors offering industry-specific DataOps, data hub and data analytics solutions. In addition, it highlights the data management priorities of industrial firms, considering what software capabilities exist to address real-world needs and how these can be combined to provide a best-fit solution. C-Suite executives, enterprise data science teams and operations managers should consider the solutions discussed in this report to support industrial data strategy.

Table of contents

Data Is Most Valuable When In-Formation, And Information Is An Unnatural State
Industrial Operations Are More Data-Driven Than Ever
Data Management Is An Increasing Priority For Industrial Firms
Introducing The Industrial Data Management Solutions Market
Solutions For Industrial Data Management Comprise Three Segments
Industrial Data Management Solutions Enable Scalable, Secure, Inter-Asset Data Flow
Industrial Data Management Solutions Have 10 Key Capabilities
Customers Must Develop Vision And Strategy Before Beginning Their Data Management Journey
Vendors Should Expand Data Acquisition Towards Varied, External Sources

Table of figures

Figure 1. Data Management Priorities For 2023
Figure 2. Industry Coverage For Industrial Data Management Solutions Providers
Figure 3. The Landscape Of Data Hubs, DataOps Platforms And Data Analytics Software
Figure 4. Industrial DataOps Platforms Orchestrate People, Assets, Processes And Technology
Figure 5. Capabilities Criteria For Industrial Data Management Solutions
Figure 6. Vendor Capabilities: Industrial Data Management Solutions

About the authors

Joe Lamming

Senior Analyst
Joe is a Senior Analyst in the Verdantix Operational Excellence practice. His current research agenda covers industrial DataOps, AI/ML analytics and applications of generative AI for industry and enterprise. Prior to joining Verdantix, Joe worked in the consumer electronics industry, where he gained experience in overseas manufacturing, product design and data science. Joe holds an MEng in Mechanical Engineering and Sustainable Energy Systems from the University of Southampton.

Malavika Tohani

Research Director, Operational Excellence
Malavika leads the Verdantix Operational Excellence practice. Her current research agenda focuses on digital technologies for Operational Excellence including digital twins and software solutions for industrial risk and asset management. Malavika has over 15 years’ experience in research and strategy consulting. Malavika previously worked at Frost & Sullivan, managing and delivering advisory projects for clients involving expansion, acquisition, benchmarking and product development strategies. Malavika holds a MSc in Economics from Madras School of Economics.

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