V2: What Makes a Great Data Analyst?
By: Joseph Burton
Tags: Learning And Development, Data Analysis, Advice, Data Science, Growth

V2: What Makes a Great Data Analyst?

Photo by Katrina Wright via Unsplash

In a recent article, I talked about what makes a great data analyst while focusing more on traits or characteristics and sprinkling in some hard skills/technologies. In this article, I will focus more on routine habits that can help you and discuss the impact they can have on your growth towards being a ‘top flight data analyst of the world, Craig!’

As a reminder, these bits of information have worked for myself based on my goals. You must first solve for what role/routine duties you are seeking. With a goal in mind, finding the path that works best is much easier.

Practice Asking Questions

You might ask yourself, ‘Why do I need to practice asking questions?’. The crazy part about this is that you just asked a question! That was quick. Obviously, you’re a seasoned veteran at this.

‘The pods that were supposed to hear this did. It’ll kick in when it needs to.’ — The Great Philosopher, Randolph Dupree

Doug Rose has one of, if not, my favorite courses on LinkedIn titled ‘Learning Data Science: Ask Great Questions’. I highly recommend it for anyone working with data, whether it’s someone coding or someone using a report that is generated or a stakeholder that looks at visualizations regularly.

Some of my favorite questions:

What will break this? It’s not just coding bugs you have to worry about. Logic bugs exist too.

It’s not just coding bugs you have to worry about. Logic bugs exist too. What will this break? As noted in a previous article, don’t be the person recommending to cut ties with a new distributor that’s skyrocketing sales just to save a few pennies on a particular KPI.

As noted in a previous article, don’t be the person recommending to cut ties with a new distributor that’s skyrocketing sales just to save a few pennies on a particular KPI. What else can influence this? If time allows, go for the fruit higher up the tree.

We can all ask questions, but do those questions close off OR encourage great ideas/follow-up questions? Strive for the latter.

Do The Same Thing, But In a Different Way

When learning to code, it’s easy to watch all sorts of videos or read tons of books, and that’s a great start. You can easily find online tutorials where you can even type in some code to check results against questions asked. Find programs that aren’t looking for a fill-in-the-blank approach.

You’re expected to be a MacGyver of sorts. A learning environment where you ‘parrot’ responses can take you only so far. Strive to be more like Emmet from ‘The Lego Movie’ and become a Master Builder. When you are more able to work in a way that you don’t need step-by-step instructions/built-in functions, you can then be more able to solve for more complex situations.

I’m not saying don’t use built-in functions. I’m just letting you know that MacGyver can do more with a shoestring, bubble gum, and dried out grass clippings than someone that only knows how to follow exact directions can with a Swiss Army knife.

Some fun practice can be to replicate built-in Python functions. It’s crazy to think, but there are multiple routes you can take to sum up 3 numbers in a list. Finding the first X amount of prime numbers is a fun one as well.

Work on solving these problems and then come back to them after more experience and solve them using a different path. Take note of the section further down about adding some notes to your work though. It’ll save you some time when you revisit these problems.

Talk About What You Do

It’s very easy and common to sort of live in your own mind. You know what you’re talking about. Can others follow your thoughts? Try it out.

Try telling someone in your circle of trust about a project you’re working on and what you are hoping to prove or disprove/discover. Talk about how you coded something with someone else that has an understanding of the language you’re using. Are responding questions extending the conversation/digging deeper, or are they quick, ‘trying to end the conversation because I’m lost’ type questions?

Going back to asking great questions, ask a colleague how to debug something. Hopefully you’re able to approach the situation with more than a ‘Why isn’t this code working?’ approach. Being able to explain what you’re goal is and the steps you’ve taken so far is a huge time-saver.

‘If you can’t explain it simply, you don’t understand it well enough.’ —Super creative smart guy, Albert Einstein

Photo by Mike Erskine via Unsplash

Document

Do this experiment:

Find a fun little, somewhat complex, problem to solve. Write a bunch of code to solve it and save 2 versions: 1 with documentation and 1 without. Plan your next steps within that problem to solve in about a month. Wait the specified time and go back and try and add to/change that code, starting with the code without documentation. Kick yourself and curse the world. Breathe a big sigh of relief because you have a version with documentation.

In the real world of data, there’s a lot going on. If you’re banking on remembering the process you’ve taken during coding, good luck. If you’re hoping to remember the ‘Why’ of your process, get ready for a ‘firenado’ of troubles.

Learn to document and remember to include things like dates or who directed changes in the final output. Once a few people leave the organization and a bug is discovered, you’d be surprised to find out how few people were involved in the initial process to offer some insight.

Take Breaks

There isn’t a single ‘type’ of break. You can take a 15-minute walk to just clear your mind a little or think of a different approach for something that’s stumping you. You can also take a day, or a few, from side projects and learning. Do both.

Just like the muscles in your body, your brain can’t go all day, e’eryday at a 100%. One of my homies recommended a great course on Coursera titled ‘Learning How to Learn’ by Barbara Oakley, and it’s great. This course mentions breaks and avoiding the ‘cram a ton into a single session’ approach.

Pump Yourself Up!

Maybe you’re going into a presentation or just not feeling super great about a recent project. Do what you can to change that.

Maybe you’re feeling pretty good and just want that extra little push.

I have the Muhammad Ali ‘I’m gonna show you how great I am’ speech down to being able to match the tone and cadence.

Have Fun

Most people don’t want an environment that feels like ‘Office Space’ when they were singing that song about a birthday. I’ve actually been at work party singing that song with the same monotone/dreary feeling!

Make some nerd jokes. They can be super creative and fun.

Final Thoughts

Data is a great, big world. There are plenty of reads out there that focus on improving your technical skills. My hope is that you’ll be able to gain a little insight into the ‘other’ part of data. As always, keep on learnin’!

Wanting to find the first article focusing on traits that help in the data analyst world?

Wanting to figure out how to show you can add value early on in your data career?