# Why you should pick data engineering

> Data engineering is a vital field that underpins the effectiveness of AI by ensuring high-quality data is available for machine learning models. This lesson explores the importance of data engineering, the evolving role of data engineers in supporting AI, and the growing demand for skilled professi…

- Web page: https://learn.dataexpert.io/lesson/why-you-should-pick-data-engineering
- Program: [The Absolutely Free Beginner Data Engineering Boot Camp starting August 14th](https://learn.dataexpert.io/program/the-absolute-beginner-data-engineering-boot-camp-starting-august-7th-6453.md)
- Access: Free — no enrollment needed
- Length: 12 min video
- Skills: ETL/ELT, Data Warehousing, Cloud Platforms
- Academy: DataExpert.io Community Academy

## About this lesson

Data engineering is a vital field that underpins the effectiveness of AI by ensuring high-quality data is available for machine learning models. This lesson explores the importance of data engineering, the evolving role of data engineers in supporting AI, and the growing demand for skilled professionals in this area. Ideal for aspiring data engineers, it highlights career flexibility, remote work opportunities, and competitive salaries, making it an attractive choice for those looking to enter the tech industry.

## Transcript excerpt

Welcome back to Data with Zach. So today we're talking about why you should pick data engineering because I'm sure some of y'all are like, isn't AI hotter? Like, why should I be a data engineer if I can just be an AI engineer, and that's like the hotter place to be. Uh, in this video, I'm gonna hopefully dispel a little bit of the hype around AI engineering as well as maybe get you a little bit more excited about data engineering in particular. So, at the end of the day, like, let's just get it right into it. Like one is What is AI, right? AI is patterns learned from data. That's what it is, like LLM Chat GPT, they, they processed a ton of data. And then that data was then looked at by giant statistical models, and then that produces what the most probable next word is. That that is what an LLM is at the end of the day. So, an LLM without high quality data. It is just crazy. It's just gonna say all sorts of random stuff. It's gonna say all sorts of things that are incorrect or not factual. And like, it's interesting because you look at uh companies like OpenAI where they spend tens of billions of dollars to ingest data from the internet, and OpenAI still has factually incorrect information. It hallucinate. all of the time, right? And so at the end of the day, like without high quality data, OpenAI and AI and LLM is just going to keep giving us more and more frustration or keep getting things wrong. So how do you produce high quality data?

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