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Article Screengrab (Image courtesy of Smart Industry)

A growing trend among manufacturers is using streaming data from IoT and other sources to mitigate bottlenecks in supply chain management. It can provide insight into customer activity and allow manufacturers to make quicker prioritization of budgets and eliminate unnecessary costs. The issue is real-time data has unique traits that are responsible for system strain when ML models analyze the data. Manufacturers can utilize newer platforms like Wallaroo with ML model compute engines designed specifically for tasks like data-stream mining, to reduce time-to-deployment and enable faster analysis.

Join Smart Industry in this featured article as they look at ”Optimizing your supply chain process using real-time streaming data

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Article Screengrab (Image courtesy of Industry Today)

Managing the large volume of products across a supply chain process requires the most recent and best available data. Manufacturers rely on various connected systems to forecast which products customers want and need. Many are leveraging this streaming (real-time) data to alleviate the challenges in supply chain management. However, real-time (streaming data) has unique traits that separate it from other types of data used in ML models. These unique traits are what make it difficult for ML models to analyze the data. Leveraging platforms designed specifically for real-time computational tasks helps to streamline your data analysis.

Explore these topics in the Industry Today article “Integrating Real-Time Data into the Supply Chain”.

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Wallaroo

Wallaroo

Wallaroo enables data scientists and ML engineers to deploy enterprise-level AI into production simpler, faster, and with incredible efficiency.