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

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275
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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Buy Your Embedded Analytics and Empower Your End-Users With the Right Data

Jet Global

While embedded dashboards create real value, they can also come with real costs. These costs are not always visible when companies plan for their analytics offering but can significantly impact production, scale, and the speed of bringing analytics to market. What Are the Hidden Costs and Challenges?

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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

In summary, predicting future supply chain demands using last year’s data, just doesn’t work. Accurate demand forecasting can’t rely upon last year’s data based upon dated consumer preferences, lifestyle and demand patterns that just don’t exist today – the world has changed.

Analytics 111
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How Encored Technologies built serverless event-driven data pipelines with AWS

AWS Big Data

Encored Technologies (Encored) is an energy IT company in Korea that helps their customers generate higher revenue and reduce operational costs in renewable energy industries by providing various AI-based solutions. All this contributes to building a scalable and cost-effective data event-driven pipeline.

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What is a Data Pipeline?

Jet Global

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

They can perform a wide range of different tasks, such as natural language processing, classifying images, forecasting trends, analyzing sentiment, and answering questions. FMs are multimodal; they work with different data types such as text, video, audio, and images.