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Creating an IoT-Based, Data-Driven Food Value Chain with Confluent Cloud

Confluent

You have food processors. Worldwide food processing machinery manufacturer BAADER sees all these necessary handoffs as opportunities to make the food value chain more efficient. We have all the tools we need to collect, process and distribute high-value events to create a true event-driven food value chain.

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The Impact of GenAI on Modernizing Food & Beverage Operations

RandomTrees

The food and beverages (F&B) industry has been transformed digitally, resulting from new technology, including GenAI. In this blog, we will look at some of the approaches GenAI has advanced in food and beverage, supported by relevant research statistics as well as real-life experiences and case studies in detail.

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US Foods Builds Digital-First Ecommerce Platform with Data Streaming

Confluent

Learn how US Foods built a digital-first ecommerce platform—using data streaming to future-proof its infrastructure and implement data mesh principles.

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Protected: DataOS Sales Accelerator for Food & Beverage

The Modern Data Company

Password Protected To view this protected post, enter the password below: Password: Submit The post Protected: DataOS Sales Accelerator for Food & Beverage appeared first on TheModernDataCompany.

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How Uber Migrated Financial Data from DynamoDB to Docstore

Uber Engineering

Each day, Uber moves millions of people around the world and delivers tens of millions of food and grocery orders. Introduction.

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Reshaping Entire Industries with IoT and Confluent Cloud

Confluent

So working with Confluent Cloud and the Kafka experts was an obvious choice,” says Stefan Frehse, Software Architect, Digitalization, for food processing machinery company BAADER. Frehse and his team are using Confluent Cloud and associated IoT technologies to build a data-driven food value chain for all their partners from farm to fork.

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Data Science in Agriculture: Roles, Application, Examples

Knowledge Hut

Food Safety Finally, Data Science is also playing a role in food safety. By analyzing food-borne illness data, agricultural scientists can identify risk factors and develop strategies for reducing the spread of disease-causing bacteria. This helps to protect consumers and ensure that food products are safe for consumption.