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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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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

When Marcus Ericsson, driving for Chip Ganassi Racing, won the Indianapolis 500 in May, it was in a car equipped with more than 140 sensors streaming data and predictive analytic insights, not only to the racing team but to fans at the Brickyard and around the world.

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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

When Marcus Ericsson, driving for Chip Ganassi Racing, won the Indianapolis 500 in May, it was in a car equipped with more than 140 sensors streaming data and predictive analytic insights, not only to the racing team but to fans at the Brickyard and around the world.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” Getting the most from qualitative data.

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And the winners are…. Congratulations to the Sixth Annual Data Impact Awards winners

Cloudera

Toshiba Memory’s ability to apply machine learning on petabytes of sensor and apparatus data enabled detection of small defects and inspection of all products instead of a sampling inspection. Voya Financial prevented millions of dollars of fraudulent transactions by deploying predictive analytic capabilities on Cloudera.

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7 famous analytics and AI disasters

CIO Business Intelligence

But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference. MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. In a statement on Oct. In a statement on Oct.

Analytics 142
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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

In smart factories, IIoT devices are used to enhance machine vision, track inventory levels and analyze data to optimize the mass production process. Artificial intelligence (AI) One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently.