 I get asked this all the time, why do I need to learn SQL if I can do everything in Python? And that's a really great question because honestly, you can do so many things in Python, you can do the data collection, the data cleaning, the exploratory data analysis, all the way to creating data visualizations and reports. The real issue starts creeping when you start work with a lot of data. Now, there are libraries like Polars and Banners that really help you work with a lot of data, even hundreds of thousands or even a million rows of data. But when you start getting past that, you're going to run to a lot of inefficiencies. And that's where SQL comes in and that's exactly what it was designed for. It was designed to work really efficiently with a large amount of data. I'm talking hundreds of millions or even billions of rows of data. So when you need to automate a process that works with 100 million rows to work overnight, to transform and clean and create a report with that data, I'm going to be using SQL every single time.