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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries.

Big Data 275
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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

An innovative application of the Industrial Internet of Things (IIoT), SM systems rely on the use of high-tech sensors to collect vital performance and health data from an organization’s critical assets. Ensure that sensitive data remains within their own network, improving security and compliance.

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12 considerations when choosing MES software

IBM Big Data Hub

Gathering data from machines, sensors, operators and other Industrial Internet of Things (IIoT) devices, they provide accurate and up-to-date insights into the status of production activities. MES systems can assist managers with process management and process control, helping to facilitate optimal performance of manufacturing.

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How data from IoT devices is changing supply chain analytics

CIO Business Intelligence

Further, the tools and devices available on the market are proprietary and prone to vendor lock-in. That is changing with the introduction of inexpensive IoT-based data loggers that can be attached to shipments. That brings us to the value of timely data and analytics. Democratization of data.

IoT 103
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Quantitative and Qualitative Data: A Vital Combination

Sisense

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.

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How Can Manufacturing Data Help Your Organization?

Sisense

Modern factories are full of machines, sensors, and devices that make up the Internet of Things. All of them generate a trail of performance-tracking data. The challenge for manufacturers is to capture all this data in real-time and use it effectively.