Mary Adenola : Data Analyst and Instructor at Code First Girls

Name : Mary Adenola

Job : Data Analyst and Instructor at Code First Girls 

Company: Aptiv

Location: Dublin

Education: Bachelors in Mathematics and Statistics from University College Dublin 

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What was your journey into a data role especially with a Maths background?

In the mathematical side of my degree, I did a lot of numerical modules like algebra and calculus but I'd never really got into the data side. The data side kind of stemmed from my statistics degree, because from the very beginning, we were introduced to datasets and the basic tools to understand them so that we would be able to find a story in the data set. And so as I progressed, I really enjoyed what I was studying in the stats side. 

There was a project that I had to do on the Titanic dataset. You know, we've all watched a movie haha. Rose could have shared that door with Jack. That was definitely a big enough door. Anyway, the question was to predict the odds of survival. I was intrigued. And I got busy using the tools I had learnt; creating graphs, creating plots, histograms, and doing statistical analysis, and looking at how gender affects survival. I found out that females are more likely to survive than men and children more likely to survive than adults. Also your class. Whether you're poor, you're from middle class or from first class, because those who were in first class had rooms close to the deck, and definitely were close to the lifeboats so they were more likely to survive. Or if you had rooms near the engine which were the first areas to fill with water. And just like that, one dataset opened the world of data analysis and data science for me. And from that day on, I think it was actually in my second year of university, I was hooked. I absolutely loved it and I've been intrigued ever since!

It’s super creative. When you're in new projects, you get to learn new softwares and new tools, so your mind is constantly being challenged. There's also the opportunity to bridge the gender gap. Tech is very male dominated so being a female in tech is also great, because you can inspire others. 

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What is data analysis?

So, let’s say my little sister has a question. So, you ask me and I give her the answer from my perspective. And then she goes to someone else, like my parents or my brothers and they give her their answers. Data analysis is having a question and trying to find your understanding.It involves collecting information from different sources, putting it together and extracting value from it. My little sister can create a story from the answers she got and come to a certain conclusion. So that's kind of it. In the simplest terms, that's kind of how I would explain it: You have a question, you gather information from different sources, you put it together and draw your own conclusion from the different answers you've collected. Hopefully that makes sense?

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What does a typical day look like?

I try to start the day with a workout, hopefully the gym or maybe a home workout. Work starts at 9 so I make sure to be at my desk by then. I have a meeting at 9:30 so usually I set up my computers and screens then look at emails from 9am till my meeting. The 9:30 meeting is a half an hour daily roundup where the team comes together, talks about what they've done the previous day and then what they're going to do for the day. Then we go into our separate little streams because we have separate projects that we're working on and collaborative projects as well. So I have meetings for one project that I'm working on which involves analyzing data for scraps materials in the company. I'd have meetings with my co-business analyst where we decide on how to showcase this data in a dashboard for other uses. So That’s 3 hours of calls, analyzing data sets and also dashboard creation then I'll have lunch. 

Over lunch, I might go for a short walk or buy some food. 

After lunch, the next four hour stretch involves me working on a project for the supply chain team. I ensure that the data gathered is of high quality and this might involve long hours spent on data cleaning. This often requires working with subject matter experts. So that's me talking to a lot of subject matter experts and data engineers, solution architects, technical leads, and data scientists as well, ensuring that our data is gathered properly, and also the data can be analysed. For example, let's say we have data relating to copper, and I don't have a background in copper creation or anything. So I'd have to go and talk to someone that is an expert in the field within the company and ask them how is this being provided and what is the process in terms of this material, going from copper to something that's been manufactured by the company and how it goes into the cars that we sell to our customers and stuff like that. These insights help us to build a dashboard for the business.

Usually my day ends at around 5. I try really hard for it not to go over. 2022 is the year of work life balance. Sometimes it's hard because we also have people in the US, which we need to have calls with and those calls might push my day a little later. 

At 6:30pm, I teach coding to a group of females who are interested in getting into the tech world. The classes are online and last 2 hours. My life is dedicated to that. I love it. 

After 8:30pm, I sign off and chill. Maybe correct a few homework assignments for like 30 minutes and if I’m lucky, I get to bed by 11pm. 

Work from home saves me on transport time of course. I’m considering a treadmill desk to keep my steps up. Occasionally, I go into the office because that makes it easier to meet people but I like the flexibility of work from home. 

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The most interesting part of what you do?

The learning! Right now, I’m learning a lot about cars and what goes into them. I really wanted to study engineering when I was going into college. I wanted to do electrical but I missed out by a few points. I couldn't do it but I continued to be interested. Being in a role that allows me to understand aspects of engineering is what I really like. I find it so rewarding. Because I get to learn about the different things that go into a car or the different components that make up something small in your car, but remain vital for the car to work. For example, last year, we were working on printed circuit boards and semiconductors, and learning how mistakes or delays at one point disrupts everything else down the line and impacts our revenue. These details thrill me. And despite being on the corporate side of things, you get to learn about the manufacturing side. 

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What’s the biggest challenge?

It’s being able to adapt to different people's personalities, especially in times of COVID. I'm used to meeting new people and making friends easily enough, but when there's someone who has a personality that doesn't really mesh well with yours, or other people in the team, it takes work to  find balance and how you can kind of manage working alongside them, even if you don’t really gel. That has been challenging, but also rewarding because it's taught me another side of myself.

Another thing is that things are constantly changing in our workspace. People are moving from one job to the other, and in the space of two months, you’re dealing with new people coming in and having to build a rapport with them.

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How does your job differ from your expectations of it?

The first thing my manager told me was, I'm going to throw you into the deep end. And I didn't really understand what he meant, but he meant deep. And so I was creating dashboards, doing deep analysis, machine learning and all kinds of projects. Then about 6 months in, my role sort of switched and I got more involved in the business side. So that's a lot of gathering requirements, translating those requirements into tech requirements, so that people in the tech roles can understand what's going on and  know what they need to build.

I thought that data scientists created dashboards, reports and plots but I actually interact with so many people, even super senior people. And it's great because I get to know every aspect of the product, whereas some people only know a certain part and some people wouldn't even know what's going on at all. 

I wasn't expecting to be introduced to new tools but Tableau and SQL are a huge part of my days. I don’t just receive data to analyse but I physically have to gather the data myself with SQL from our database, actually learn how to use the command line interface. I just keep adding to my skill set. All the opportunities and responsibilities that I've been given overwhelm me. But I have also stepped up. Now, my manager reminds me to take it easy. 

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What are necessary skills and strengths for someone to have or develop if they want to be a data analyst?

You need to be inquisitive. That is the number one trait. When I first joined, I didn’t ask enough questions and now I don’t care who I’m talking to but I ask as many questions as I have. 

You also need the toolkit; applications like Tableau, Python and SQL are necessary requirements alongside a solid foundation in statistics and data analysis. 

Other useful qualities are good communication skills, teamwork, and being able to ask questions, like I said, but also being able to be heard. The environment around you may change so you need to be able to adapt to the different circumstances that you might face or the problems that you might encounter. 

Google is your best friend. 

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What's the best advice you've ever gotten? 

And to be honest, it's to believe in myself. It's quite common to get imposter syndrome. I remember last year, for a good three to four months, I felt like I was not supposed to be in this role. And I found everything hard. I was like, “Am I doing this correctly?” Even though I was being reassured by my manager, I remember that I would leave work and cry. At the start of work days, my heart would race. It took a while to calm down but I realized that, if I'm finding something really challenging, that's where I'm supposed to be. And I had to believe in my skills and what brought me to this opportunity. Always remember that you're here to learn and the world is your oyster. It's vital for you to learn as much as you can. This will propel you to the next role. And so that's kind of the main advice that I would give, that was given to me and I would give others, is believing in yourself. Because where you are, despite it being challenging, is where you're supposed to be. That's it.

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What would you do differently if you could start over?

Education-wise, I probably would have paid more attention to what I was learning than what I did. While I got a first class degree and all, that doesn't mean that I actually fully paid attention to some of the modules that would have really helped me now. In my spare time, I’ve done a lot to catch up. I also wish I had done an internship. I wish I had committed to doing something each summer because that prepares you for tech job interviews, gives you skills and experiences and  also builds your portfolio.

Currently, I am always hoping to do more projects. At the moment, I’m super interested in doing more software engineering, getting really hands on in building programmes, interfaces and whole architecture systems. It's the change I want to make.

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