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How Can Manufacturing Data Help Your Organization?

Sisense

The modern manufacturing world is a delicate dance, filled with interconnected pieces that all need to work perfectly in order to produce the goods that keep the world running. In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. It’s easy to see why.

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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

Smart manufacturing (SM)—the use of advanced, highly integrated technologies in manufacturing processes—is revolutionizing how companies operate. Smart manufacturing, as part of the digital transformation of Industry 4.0 , deploys a combination of emerging technologies and diagnostic tools (e.g.,

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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

NTT, which partners with Penske Entertainment for the NTT Indycar Series, including the Indy 500 race, collected an estimated 8 billion data points through the sensors on Ericsson’s car and that of his 32 competitors.

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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

NTT, which partners with Penske Entertainment for the NTT Indycar Series, including the Indy 500 race, collected an estimated 8 billion data points through the sensors on Ericsson’s car and that of his 32 competitors.

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Eight Top DataOps Trends for 2022

DataKitchen

If data analytics is like a factory, the DataOps Engineer owns the assembly line used to build a data and analytic product. Most organizations run the data factory using manual labor. The Hub-Spoke architecture is part of a data enablement trend in IT. Rise of the DataOps Engineer.

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12 considerations when choosing MES software

IBM Big Data Hub

Manufacturing execution systems (MES) have grown in popularity across the manufacturing industry. If your manufacturing processes have become more intricate and challenging to manage manually, an MES can help streamline manufacturing operations management, increase efficiency and reduce errors.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. You can find similar use cases in other industries such as retail, car manufacturing, energy, and the financial industry.