Q at a high level, how does, how does, how do, some of you mentioned it, mentioned a little bit about it, but how does that work? What's the stack? What's, I mean, I don't know, are you like Hadoop users? What's, what, how does it work behind the scenes? How do you compute the, and, and process large amounts of data, and provide the insights? Whoever wants to go first.
A I can go. So, uh, we're, we're not using Hadoop. Uh, actually we found that, uh, Hadoop and most, kind of, no, no SQL solutions are, are not very good for, kind of, quantitative data when you need to aggregate and, kind of, go across these things. Uh, we're, we're using Postgres, actually, as our database. We, we don't have a typical setup of it. Uh, probably a pretty, pretty advanced one. Uh, but, you know, that, that, that, that's, that's what we use underneath that. Then, kind of, the stack goes up and, uh, It, it's fairly typical for kind of, for web, web applications when, you know, apart from that, so backend written in Python, all the kind of, all the, ah, all the data connectors and everything on the server side, Django, and then heavy JavaScript and HTML five stuff on, on, on top of that. So the, the kind of secret sauce is, or where we've spent most of our effort is probably in the database model and the kind of, the, the really low level stuff, And then in making this really usable and, like, really approachable for, for end-users at the top. So, visualization, JavaScript, UI stuff.
AI assessment note: “we're not using Hadoop... we're using Postgres, actually, as our database.”