What is the most challenging thing about the Data School?

by Gwilym Lockwood

It’s self-reflection blog week at the Data School, and today’s topic is “what is the most challenging thing about the Data School?”.

That’s a hard one, to be honest. It’s difficult to sit here and think of something that’s genuinely challenging, because as soon as I write it down, it seems like quite a petty gripe. For example, a few minutes ago, I typed out (and then deleted) “the documentation online for Tableau and Alteryx isn’t that great”. It’s not, and it does make working out how people have created their dashboards frustrating to replicate, but that’s not exactly a problem with the Data School.

Perhaps the most challenging thing is that you only get out what you put in. The Data School isn’t a magic course where you become an excellent consultant just by being there for eight hours a day. You have to put things into practice yourself, which means finding your own side projects to work on and finding your own data to play with. There’s only so much you can do with Tableau’s Superstore sample dataset; you’re not going to learn anything properly unless you contextualise it with something outside work. And your first attempts aren’t going to be great – mine weren’t, and my current attempts have a lot of room for improvement – but that’s how you learn. Andy’s Makeover Monday project is a great way of trying things out and contextualising your Tableau skills, even just for an hour or two a week.

But on the other hand, if you like what you’re doing, it doesn’t feel like work. It’s more like the Data School gives you the tools to answer the questions that interest you.