Learn more about Laine's experience, from the time she applied to The Data School, to her career as a Product Manager at Alteryx. Laine was part of Cohort 9 of The Data School London, which took place from June 2018 to October 2019.
Interviewed by Mel Niere | Edited by Vivian Ng and Laine Caruzca
Before The Data School
Q: What brought you to The Data School? What factors influenced your decision to apply and ultimately join The Data School?
Before I joined The Data School, I had just graduated from university with a degree in International Relations and wanted to do international development, so I spent three months in Bangladesh and came back wanting to get some really tangible skill sets, in order to return and do more with international development later on.
During that time, I realized that I really liked problem solving and consulting; I liked working on a project-by-project basis, as well as being the one to think of a solution and working with other people to get it implemented. I looked for consulting jobs when I came back to the UK, and The Data School was one of the only ones that didn't have too many prerequisites. For someone who hadn’t had too much consulting experience, that was probably the most attractive part of it—in addition to the free pizza at the Meet and Greet.
But really, what got me hooked were the people at the Meet and Greet. They all just felt so passionate about what they were doing. There was an aura of go-getters, entrepreneurs… people who wanted to just solve things on their own. I knew this was the environment I wanted to be in, a place I wanted to grow in, and these were all people I knew would push me to become better.
During The Data School
Q: What was your training experience like?
I really enjoyed the weekly client projects. You had to produce something at the end of the week, which made me feel like I was progressing. I became more confident presenting and finding the best way to communicate the stories that we found within the data. Not only that, I liked working together in groups because it allowed us to understand each other's strengths and weaknesses and figure out the best way to work with different personalities. It was a really good exercise in both team-building and self-awareness.
The community is probably one of the biggest plus of the program. The Data School is so integrated with the Tableau community. There were also opportunities to create your own communities, like User Groups and Data+Women. Being exposed to all of these different groups allowed me to feel like there was impact elsewhere, not just in the classroom; I met so many different people and expanded my network.
More importantly, The Data School encouraged us to build our own brands, and that's something that I really, really loved about the program. I started thinking about these questions: How do I want people to know who I am? How do I create a good reputation by creating my own blogs, my own content? What other roles are people doing? And how can I emulate some of those things to represent what I really wanted to do at the end of the program?
Q: How did your placements at The Data School enhance your skills and knowledge?
The Data School pushed me to do placements in a variety of different industries and a variety of different roles. My first placement was at a sports betting company, Sporting Index. I knew nothing about sports or betting, but I knew Tableau, and my role was to increase adoption of Tableau across the company. I really loved that because it gave me the space to own that role; I was able to think of creative ways to increase engagement across the company by releasing content that was relevant but also technically helpful for those who were just starting out.
At the time, Convo was probably my biggest lifeline of support [editor's note: The Data School’s internal social media platform]. Every time I did something good, I felt really celebrated. I felt like I could talk about it on Convo. When I had issues, there was always somebody who could help out and offer an external perspective that allowed me to see something that I couldn't have seen by myself.
My second placement was at BCG, which was Alteryx-heavy and really technical, a nice balance from the Tableau-heavy placement at Sporting Index. My third and fourth placements were at PwC, but in different departments. The first one was in Deals Tech, where we worked on client projects as well as internal ones. The second one was focused around business restructuring services, where I was given the opportunity to explore other technologies such as Python, Machine Learning, NLP and low code app platforms such as Mendix and PowerApps.
Ultimately, these experiences got me the job at PwC, which then opened up a whole load of other doors for me and got me to where I am today—back at Alteryx.
After The Data School
Q: How did The Data School and The Information Lab serve as a launchpad for your data analytics career?
Without The Data School, I probably would not be where I am today—or as quickly—without the connections I made at PwC. I didn’t get a job in just Tableau or Alteryx, but in something else that I was interested in—expanding my tech toolkit to include Python, a bit of coding, some natural language processing models. I built some of that at PwC and ended up in a team that did software development, which was ultimately what I wanted to do at the time. I wanted to solve more problems than what Alteryx and Tableau could solve; I wanted to develop technically via all those tools.
After The Data School, PwC opened up all these other doors that allowed me to explore other technologies. I bounced around different teams and learned many different skill sets, before getting into product management, straddling the line between the technical and the business needs. I really enjoyed understanding and answering: Why and what do we build?
My job at Alteryx is basically all of my experiences wrapped up in one role—product management. I have in-depth knowledge of Alteryx as a product itself, how customers use it, and how it empowers organizations. I also have an understanding of the pain points and value propositions of the tool from my various experiences, and get to speak to the developers a lot now, but on the coding side, which I also really enjoy.
Advice About The Data School
Q: What advice would you give to individuals considering applying to The Data School?
Do it. If you're having doubts, just throw yourself in there. I think The Data School is all about throwing yourself in the deep end and pushing yourself. If that's the kind of environment you want to be in, and you really want to learn, and you really want to launch your career in a really important industry—where there's a big need, which ultimately leads to job security—then I'd say you literally have nothing to lose.
My advice to someone who is applying is to reach out for help. For me, the biggest help has been the network that I've been able to create—not just the network of people that I can rely on to help me solve something technically, but also, ultimately, to get me a job and position that I want to be in that I think would have been harder to get if I’d had to go through a different route.
The Data School gives you a lot of that help and community. As I said, I wouldn’t be here without them. The biggest part of that is just getting to know people and to build good connections with them. Finally, trust that with you coming from The Data School, which has a huge reputation for delivering high-quality candidates, there's really no kind of limit to where you can go.