Analytics & Machine Learning

The use of analytics in industrial companies is growing rapidly.  For more than a decade, the information workhorse has been the business intelligence (BI) platform, supplemented by enterprise manufacturing intelligence (EMI) in the plant.  These systems excelled at helping users discover and understand the underlying reasons and details about what happened and why.  Now, with the industrial space becoming much more dynamic, manufacturers are turning to advanced analytics and machine learning to support predictive and prescriptive solutions. 

Today, the analytics market is extremely fluid.  More companies are pursuing analytics solutions and more employees throughout the enterprise want more and better decision tools.  And the increasing focus on Industrie 4.0 (I4.0) and Industrial Internet of Things (IIoT) is driving demand for predictive maintenance solutions, which rely on advanced analytics.

Industrial companies can benefit from enhanced insights into market demand, operations, inventory, and corporate performance. Analytics provides the information to effectively manage global markets, supply chains, and operations. 

Use of Machine Learning, Artificial Intelligence, Cognitive Computing Is Exploding

Artificial intelligence, or machine learning, underlies many now-common consumer products.  Netflix recommends what to view; Siri, Cortana, and Alexa respond to voice; and Amazon uses this technology to optimize product recommendations.

In the industrial space, we’re seeing considerable interest in using these technologies to optimize asset maintenance, production operations, supply chain, product design, field service, and other areas.  Being interested is one thing, but understanding how to obtain and use the technology for a specific purpose is quite another.  ARC analysts can work with your team to help select the right technologies for your specific applications.


ARC Coverage Areas


    ARC's team of analysts are dedicated to researching, analyzing, and consulting in these areas:

    • Artificial Intelligence
    • Big Data
    • Business Intelligence Platforms
    • Cloud Application Platforms
    • Cognitive Computing
    • Enterprise Manufacturing Intelligence (EMI)
    • Machine Learning
    • Predictive Analytics
    • Prescriptive Analytics


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