Last week I completed and passed the Tableau Desktop Associate Certification. This marks a significant milestone in my professional journey. This certification is confirmation of a recent career shift, validation of my ability, that the hard work and many steps I took to get here were worth it, and that I’m officially in the right place. It’s been a winding road to Tableau and I’d love to recap some of the triumphs and troughs with you.
Like many others, with the onset of the COVID-19 pandemic I experienced an entirely new way of working and faced new challenges that provided insight into the parts of my job I enjoyed and the places that could use improvement. Leading up to 2019, I had spent the past seven years teaching robotics, engineering, and biomedical science at private college-prep high schools, and spearheaded some big programmatic developments. It was pretty awesome to feel like I could inspire young people, and I liked my job most of the time. I had minimal Sunday Scaries, and didn’t dread going to work in the morning.
Alongside the teaching I was doing, I began a side-hustle working on web development, which provided me with the opportunity to wrangle my own clients, work on project requirements, develop clear project management, and tackle business needs with my own LLC. Plus, it was an excuse to stretch my learning in a new direction.
It was a lot to handle during regular times, but when COVID hit and we were asked to teach from home, it became clear to me that teaching wasn’t my end game and only heightened the cons of the job. I began to consider new careers and figured I could continue the things I loved about teaching high schoolers on another path. My priorities to transition were things like coaching, continuing education focused on adults, and pursuing some of the learning that kept me in a flow state, primarily programming and solving tough problems. I did a ton of career searching and aptitude testing and began talking about a career switch with my friends.
I have always been interested in easy ways for people to engage with data, both in the classroom and with my colleagues. Usually, this would be in the form of infographics. Up to this point, I hadn’t put much thought into how to make infographics interactive, so, when I first saw the New York Times COVID Dashboard, I dug into how they made it. I realized it was within reason that I could build something like this. I had a background in tech, had a few years of programming experience, and enjoyed making data-driven decisions.
I loved the interactivity of the dashboard and how there were both forecasts and trends available. The option to begin at a global scale and then drill down to see infection rates in my community was really helpful to understanding something that felt very scary and unknown. The dashboard was a comfort to me and brought me out of the dark to see what was going on while I was isolated at home.
As I did more research, I learned that at first, the analysts weren’t able to pull this information straight from a single source. They had to do a lot of backend work to get the data to play nice and be able to bring in data from different states and counties with different formats. I was fascinated by this process, and how someone would go about gathering all of the information from various sources, especially when it felt so urgent and crucial to public knowledge. I was equally amazed at how it was put together in a way that was so easy for viewers to understand (even if they had a low data literacy, it was obvious that there was an increase in cases in the United States and globally).
To understand more about how the dashboard worked, and how I might turn this interest into a viable career option, I looked into some of the skills required to perform a job in data visualization, and analyzed how they compared to the skills I’d been using for years as an educator and data scientist. I noted observations about the dashboard, and compared them to my skills at that time.
From here, it seemed reasonable that I could attain the skills I needed.
As I planned my approach to this transition, I zoned in on utilizing my network and my resources. I engaged in over twenty informational interviews to ensure I was entering a career field that I’d be interested in for the long haul, spent over 200 hours engaging with course work on DataCamp to build the skills I needed to be successful, hired a career coach, had formal resume reviews with professionals in the field and my alma mater, and put my interest on social media blast. I even hired a LinkedIn expert to pump up my visibility and constantly reminded myself to remain open to whatever offerings were available.
I wanted this change, and I wanted it BAD.
The informational interviews and career coaching helped me understand what sort of company I wanted to work for and what work I’d be interested in within the umbrella of data. It made me laser focus on applying exclusively to companies that fit my values. It also gave me the confidence to reach out to local data groups in the Twin Cities (I’m looking at you WiMLDS and She Talks Data) to grow my network and feel comfortable asking for advice.
At this point, I was feeling pretty confident I could do the work and I had put over six months into this career change, scheduling one to two hours every evening and dedicating myself to a few hours with my morning coffee on the weekends skilling up and revamping my resume. I dedicated ten to fifteen hours a week to skilling up. It became my evening activity, and the best part? I really enjoyed it. The learning was like a good book, I couldn’t put it down.
A career switch not only requires serious after-hours commitment but can be incredibly intimidating and is often accompanied by humbling self-realizations. It took a lot of conversations with myself to understand what I was searching for in a job. I knew I wanted something that was fast-paced, challenging, and human-centered, and I wanted to continue to work in tech. I knew it was incredibly important for me to have the opportunity to continue learning on the job to stay on top of my craft. Perhaps the hardest part was imagining how I would achieve those goals.
I told myself to continue taking action to get one step closer to changing careers. Even if I wasn’t certain of the exact path I would take, I had a general direction and that would suffice. Sometimes they were small actions like sending an email to an old friend or asking for connections on LinkedIn. Others were a little larger commitments like a career track on DataCamp or scheduling a block of time for a coding challenge. Each action brought me one step closer to the ultimate goal, each step was positive reinforcement that I was headed in the right direction.
The fit is undeniable. I get to work with a dream team of other high-achieving (but not overworked) colleagues in a collaborative and supportive environment.
Even with an untraditional path to this role, I believe my skills and interests align naturally to this kind of work. Below, I’ve narrowed down a list of the attributes that I believe ultimately led me to this new data-driven path:
Maybe you feel the same way and have similar skills and interests. If so, perhaps a career in data analytics consulting may be for you!. Everyone’s path will look a little different based on experience and interests, but a change is always possible with a little strategy and a genuine dedication to growth. My best advice is to lean on your community, don’t be afraid to reach out to your network, and invite yourself to some meetups along the way. Soul searching is definitely a part of the recipe, but sometimes there are questions you can’t answer without doing the job- which is where those informational interviews come in. Sure, it’s important to ask about how each person got to their current role, but be sure to leave room for the tough and uncomfortable questions, too.
It’s strange to think that a year ago the first inklings of a career shift were creeping into my daily thoughts. I am so proud to have a crew of amazing DataDrivers to support and encourage my growth as a consultant. The learning doesn’t stop here, and I can’t wait to continue this journey. No matter where you find yourself in your data-driven journey, it’s a matter of matching up the right tools for the right job. Whether that’s answering 6 questions to help you answer if you should go into analytics consulting or skilling up for your first Tableau Certification, DataDrive has some great resources to get you started on a transition to put data first.
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