Here's your guide on your journey into data!
Jennifer Seaton is a Data Analytics Instructor here at Juno College. She specializes in developing gamified educational environments, and has received a PhD for her research into how games can increase student engagement in online courses.
Her passion for improving online education inspired her to learn programming — she's since fallen in love with it, and loves teaching programming to others! Outside of work, you can find her reading, writing, and playing video games.
Learn more about why Jennifer loves working with data, how to tell if a data career is for you, and her advice those looking to get into this booming industry!
Juno College: When did you first start dabbling with data?
Jennifer Seaton: I come from an academic background, so most of the work I did involved working with and analyzing data. I got more interested in data analytics when I realized the power of data visuals to communicate analysis in a user-friendly way.
JC: What do you enjoy most about working with data?
JS: When you get a raw data source, it is just a jumble of information. You generally can make sense of it just by looking at the individual entries. But during analysis, you can find trends and discover the story that the data has to tell. It is this sense of discovery that I find very rewarding. Even more so when the lessons from the data can then translate into real-world applications.
JC: What are some of your favourite data projects?
JS: Since I'm an educational researcher, any data visualization that helps an instructor teach better or a student learn better is always super fun!
Check out this list of Cool Data Analytics Projects for some examples!
JC: If someone is considering a career change, what are some signs that they may enjoy a career in data?
JS: If you find that you can’t help but dive into the nitty gritty of any interest of yours, then playing with data can be very rewarding. For example, I have recently learned that I prefer 16g of coffee beans in my aeropress coffee as opposed to 18g. This involved tracking a variable and finding a trend. I was not dealing with a large data set, but it is that mentality of finding comfort in data and numbers!
JC: What advice would you give to someone looking to pursue a career in data?
JS: I think an important step that many people overlook is to start by understanding what skills/knowledge you already have and bring to the table. Domain knowledge is very important when working with data. Bringing domain knowledge, soft skills, and technical skills is a winning combination.
JC: What sets apart Juno’s Data Analytics course from other learning options?
JS: Honestly, it is the other students in the class. One of the hardest parts about moving into another industry is networking with peers. That important job skill/opportunity is built into Juno's Data Analytics course. I also think that the focus on diversity at Juno helps to make reaching out to the other students less intimidating.
JC: Your PhD research focused on how games can increase student engagement in online courses. How has this impacted your teaching?
JS: It impacts every aspect of my teaching. I strongly believe that there is no such thing as a “bad student,” only poor learning environments. A very important aspect of a good learning environment is the freedom to fail. We see this in video games. You can try a level over and over again. You don’t worry about losing, because the process can help you to learn what you have to do to get it right the next time. I try to support this mentality in my teaching.
JC: What would surprise people about working with/in data?
JS: The biggest myth is that data is objective and/or neutral. Every step in gathering and analyzing data is value-laden and biased. This is why it's so important to improve diversity in the field!
JC: Who and/or what inspires you in tech?
JS: I'm probably an oddity in that I think that past research from the '50s to '70s is super interesting. There are a lot of ideas that are theoretically sound but they didn't have the resources or computing power to fully explore. Often I find that the future is written in our past.
JC: What kinds of trends/developments do you think we can expect from the data/tech industry in the future?
JS: I don’t know. The field is still very new, and has a lot of growing up to do. I think right now the biggest concern is creating ethical frameworks and understanding how to make the field less biased. But as far as fun developments, I think that augmented reality has a lot of potential. It will be interesting to see if that takes off.
Ready to dive into data?
Jennifer teaches our part-time Data Analytics course, where you'll learn to analyze data, fast. Through a perfect blend of interactive lessons and hands-on practice, you’ll master the fundamentals of data analysis and explore industry-leading tools and languages like Google Sheets, SQL, and Tableau. Beginners welcome!