The Data School has not disappointed me.
These first few days have been everything I expected—intense, instructive, and a little overwhelming, though in a good way. So far, we covered introductory topics that have already crashed my internal memory: data visualization best practices, data types, sets, choosing the right chart (i.e., staying as far away as possible from tree maps and pie charts), data cleaning, modelling and prep.
What I didn’t expect was how often I’d find myself connecting these technical concepts to things that show up in places outside Tableau and have nothing to do with dashboards and data sets. I can’t help but link them to something real, often something personal: prioritising house chores and data hierarchies, dealing with the mental load of being a working mom and cleaning messy data, and figuring out which join type best suits my family’s schedule.
Where data meets life
This N-part blog series will focus on the intersection of lived experiences and data principles. Each post will take a part of (my) life —uncertainty, chaos, love, motherhood, identity, etc — and pair it with a data related concept.
I aim to put a more human lens on technical things and show how, if you put your analyst mind to it, you can see that some of these concepts are part of our daily life, even if we don’t call them by their name.
What to expect
For all those technical-blog-lovers out there, I’m sorry to disappoint you. There will be no tutorials on how to make complex and visually appealing charts— which is probably in your best interest given that I’m just a data analyst in the making with a lot to learn.
But don’t worry, this will not be an abstract blog about my feelings either, I will still offer some practical value.
I’ll try to break down data concepts in ways that make them approachable. Sometimes I will write a step-by-step type of post, other times I’ll share how I understand these concepts, how they work or what to keep in mind when dealing with them, and some other times—hopefully not too often— I’ll may complain about how they made my week difficult.
Why does it matter (to me)
I like it when things make sense, and every piece is in its rightful place. Unfortunately for me, life doesn’t usually work like that, which is probably why I’m drawn to data in the first place.
Sure, data can be messy, but so can life. At least with data it’s easier to sort out the mess (right??)
This will be my attempt to connect the dots outside the classroom, turn them into real life knowledge.