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The State of Data Engineering at Data Day Texas 2024

Jesse Anderson

The premier of my latest talk covering The State of Data Engineering. This starts with data warehousing and goes into data science. I finish off by showing how data engineering can avoid the same fate as data warehousing and data science.

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GPT and LLMs from a Data Engineering Perspective

Jesse Anderson

There has been quite a bit of writing covering GPT and LLMs from data science and business perspectives. I haven’t seen much from the data engineering side. Let me share my perspective, having been in data and AI for a while and using LLMs before they became popular. How can we use LLMs in data engineering?

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Mr. Pavan’s Data Engineering Journey Drives Business Success

Analytics Vidhya

He is an experienced data engineer with a passion for problem-solving and a drive for continuous growth. Thus, providing valuable insights into the field of data engineering. Introduction We had an amazing opportunity to learn from Mr. Pavan.

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Data Engineer vs Data Scientist: Which Career to Choose?

Analytics Vidhya

In the world of data, two crucial roles play a significant part in unlocking the power of information: Data Scientists and Data Engineers. But what sets these wizards of data apart? Welcome to the ultimate showdown of Data Scientist vs Data Engineer! appeared first on Analytics Vidhya.

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Brief History of Data Engineering

Jesse Anderson

As clearly evident as that sounds now, my writing about needing data engineering went heavily against the grain of everything that was written at the time. DJ Patil coined the term Data Scientist in 2008. For the majority of companies, that was the only title working on data problems at scale.

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How I use Gen AI as a Data Engineer

Towards Data Science

In this article we dive into some practical examples for Data Engineers Continue reading on Towards Data Science » Generative AI is all the rage.

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7 Data Engineering Projects To Put On Your Resume

Seattle Data Guy

Starting new data engineering projects can be challenging. Data engineers can get stuck on finding the right data for their data engineering project or picking the right tools.