Q right? Your SQL editor notebooks, which touch on R and Python and reports and dashboard. You then choose to sort of package those in unique ways across three separate types of pricing plans, studio, business, and enterprise. But then you also have like, you know, in a, you know, the Helix data engine, for example, how do these things all work together to make up a pricing plan for mode?
A Yeah. Um, I'll back up and talk about just some of the, the basics of how we think about it. But the first thing is, um, it's, it's really one product. Uh, it has a bunch of features that are tied together, but the important thing, and this will always be the case, right? I don't ever want to separate SQL from, you know, Python in mode because the point of the product is that you can move seamlessly between the two. If we break those into separate a la carte items, you know, I don't want our customers to have to choose. And a big part of the reason is, Folks don't realize exactly what they're going to use before they start using it. And a lot of what we've done with our interface enables people to level up into jobs that they didn't know they could do or hadn't done before, right? In the Python world, if you want to set up Jupiter, right? This is the standard tool people use for Python for data analysis, right? You set up this Python notebook on your desktop. The fastest way to do it is using a product called Anaconda, uh, It's still hard to do. Like, it'll take you half an hour with someone who's done it before sitting next to you pointing out how to do it. Whereas if you want to use Python to do like a very simple, the example I always use is median, right? So SQL is a really bad tool for calculating a median. In Python, it's like trivially easy. It's just one line of code. S…
AI assessment note: “it's really one product... If we break those into separate a la carte items”