Chapter 1: Who is a data analyst, why read this?

This book is about my experience becoming a data analyst. I’m not in any definition an expert. I’ve worked at exactly two different companies as a data analyst, with a slew of data interviews (mostly successful, some not) under my belt. This is just one path you can take if you’re looking to transition into a data analyst career. Call me biased but I think it’s one of the most meaningful, impactful and future proof jobs out there right now.

I have distilled of some of the things I’ve done right and the many things that I wish I had done better. To make it applicable, I’ve made the lessons into generalized principles while giving specific examples. The principles and lessons I learnt are all blatantly stolen in some form or other from the giants on whose shoulders I stand on - thinkers, writers and doers who’ve been around the block several times over. I’ll link the resources that I have greatly benefitted from where possible.

Who is a data analyst?

A data analyst is someone who uses data to make a smart decisions. This means getting the business to take action that has the highest chance of success. What is success? It’s likely going to be increased profits, either by growing revenue or decreasing cost.

To the layman, a data analyst is synonymous with data scientist. In reality and in large companies, data analysts and scientists have completely different scopes. A data analyst is the expert on both data and the business. Someone who is better at data than anyone in the business, and someone who is better and understanding the business than anyone in the data team. The goal? Guide and influence strategic business decisions to get the best outcomes.

Why would you want to be a data analyst?

I’ll assume you have some interest in data, hence you reading this book. This is the section where were focus on why be an “analyst” vs “scientist” or “engineer”, and why data instead of other careers.

Data is impactful

One way I think about a career is how much difference I am going to make. At the risk of getting philosophical (bear with me), our time on earth is fixed and it’s what impact we make during our lives that matters. A data analyst is the person leaders approach to make informed decisions. These are big decisions that can impact millions.

My first data analyst role was in the marketing team for a fashion e-commerce company. How much impact does a marketing team have? We were sending over two billion messages a year to more than ten million customers. This brought it millions in revenue per year. I was the only data analyst, and optimizing these messages by only a few percent brings in a lot more revenue. Even though the impact per customer was small, I was literally influencing millions of customers. In aggregate, that’s big.

I find having impact fulfilling. It gives me a reason to do mundane things when I step back to see the bigger picture.

Change industries easily

I absolutely love having options. I don’t like the idea of being stuck in a sunsetting industry. Technology moves really fast and I’ve learnt that riding the wave and jumping on the bandwagon will make your life a lot easier.

I’ve switched companies once in my 4 year span as a data analyst. It was from ecommerce to fintech. The business knowledge I’ve gained in ecommerce is completely useless in my current role, but the data skills I’ve picked were fully relevant. It was a tough learning about fintech in the first two months, but I felt like a fish in water when looking at new datasets.

Having transferable data skills gives you options. Besides the fintech company, I had other offers in a tech travel company and a large tech ad firm. All different industries. If you’re unhappy with the current industry or company culture, quit. Change. Go to a completely different industry with a different culture. The transition is easy as long as you have the relevant data skills.

Having options before you find something you absolutely love is important. We have to first explore before we begin to exploit opportunities that we love.

Futureproof yourself

A huge part on why I took the risk and switched careers was because I feared becoming obsolete. There’s this exercise called “Envision your future self”. It’s where you imagine yourself 10 years older. How are you spending your days, what impact do you have on the world, and what regrets did you have in the last 10 years. Projecting this far out helps you make optimal decisions in the long run. It helps avoid the comfortable trap of just going where life takes you. We have one life and we should own it. Don’t let the default and comfortable path prevent you from living your best life.

Quitting a job without anything lined up is scary. It’s even harder when I think about the new skills I’ll have to pick up and interviews I had to go through. But sometimes, we just have to bet on ourselves. After all, what’s the worst that could happen?

I found Jeff Bezos’ regret minimization framework immensely helpful. In the long run, I knew a career in data will open far more opportunities than my current path. Most if not all companies are moving to a data driven culture. Sooner or later, all positions will involve some form of data. I want to prepare myself for that eventuality and I knew my opportunity cost was only going to grow the longer I waited.

I was not going to regret trying and if I failed, I wouldn’t regret that either. The only regret was not having tried. That made it an easy decision.

My background and what should you care?

We’ll eat the meat of the book right after this, but one more quick detour. Who am I and why should you care?

I’m Jo. In my past life I was a finance major and a mergers and acquisitions analyst. This meant advising private equity firms if they wanted to takeover new companies, or if they wanted to sell existing companies in their portfolios. In 2017, I quit my job to become a self-taught data analyst. It took me less than six months, but boy those were some of the best times of my life. I woke up each day having a purpose, knowing I’ll be doing something meaningful. It was a feeling I haven’t felt before. Through that time, I taught myself how to code, learnt some data stuff, and honed my interview strategy. I wrote this ebook to share my learnings. I hope you’ll benefit too.