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

AWS Big Data

This post is a guest post co-written with SeonJeong Lee, JaeRyun Yim, and HyeonSeok Yang from Encored Technologies. 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.

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The case for predictive AI

CIO Business Intelligence

Predictive AI uses advanced algorithms based on historical data patterns and existing information to forecast outcomes to predict customer preferences and market trends — providing valuable insights for decision-making. It leverages techniques to learn patterns and distributions from existing data and generate new samples.

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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. Did you know?

Big Data 275
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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

Understanding Healthcare BI Tools The Role of Healthcare BI Tools Healthcare BI tools are instrumental in revolutionizing decision-making processes and patient care through the utilization of advanced data analysis and technology.

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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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How data from IoT devices is changing supply chain analytics

CIO Business Intelligence

A McKinsey study on the impact of this extended disruption found something very interesting: while 75% of companies surveyed faced problems with their supplier base, production and distribution, 85% said they struggled with “insufficient digital technologies” in the supply chain. The solution?

IoT 105
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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. Leveraging data where it lies.

Analytics 109