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I asked ChatGPT to write a blog post about Data Engineering. Here it is.

Confessions of a Data Guy

Data engineering is a vital field within the realm of data science that focuses on the practical aspects of collecting, storing, and processing large amounts of data. Here it is. appeared first on Confessions of a Data Guy.

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Building A Data Mesh Platform At PayPal

Data Engineering Podcast

Jean-Georges Perrin was tasked with designing a new data platform implementation at PayPal and wound up building a data mesh. In this episode he shares that journey and the combination of technical and organizational challenges that he encountered in the process. We feel your pain. It ends up being anything but that.

Building 147
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Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

Process 119
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How BI Can Inform Your ERP Selection Process (Manufacturing)

FreshBI

The purpose of this blog is to provide an example of how a manufacturing operation can use Business Intelligence (BI) anchored in its economic engine, to inform the ERP selection process. How Business Intelligence Informs Your ERP Selection So, back to our purpose for this blog - how to use BI to inform my ERP selection process.

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Building a Chatbot Using Prompt Engineering

Edureka

In other words, you don’t need to be a programmer or have any coding background to dive into this creative process of building a chatbot using prompt engineering. We’ll start from the ground up with Flowise, guiding you through each step to build your own AI persona chatbot.

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Expert Roundtable: How to Build Real-Time Personalization and Recommendation Systems

Rockset

I recently had the good fortune to host a small-group discussion on personalization and recommendation systems with two technical experts with years of experience at FAANG and other web-scale companies. Nikhil Garg is CEO and co-founder of Fennel AI , a startup working on building the future of real-time machine learning infrastructure.

Systems 52
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Building Real-time Machine Learning Foundations at Lyft

Lyft Engineering

In early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving , training , CI/CD, feature serving , and model monitoring systems. However, streaming data was not supported as a first-class citizen across many of the platform’s systems — such as training, complex monitoring, and others.