With a lively crowd of over 50 members, our Toronto chapter of Women in Big Data had their first meetup on June 13, 2018! During the event, we uncovered the different roles and functions that work with big data. We also explored how different industries interact and use big data through an interactive panel discussion.
Lilian Lau, the Director of the Toronto chapter, kicked off the event with the goal and mission of Women in Big Data. Lilian spoke about Quandl’s data pipeline as an introduction to the different roles and teams that work with big data. Quandl, the sponsoring company of this event, is a marketplace for data for professional investors. Lilian described the functions of each team: the supply, data research, data engineer, marketing, sales, operations and development team. Participants learned the differentiation between data scientists and data engineers as well as the importance of context when working with data.
We then turned it over to our three panel speakers from various industries: Alessandra Fraquelli from the business and consulting space, Joanna Yu from health science research and Vanessa Feng, who is a machine learning data scientist. The panel discussion took on a life of its own, with participants actively asking questions and befriending our panelists.
Alessandra highlighted the challenge of fragmented data ownership within organizations, where data is often stored in silos and in different structures. She also spoke to the structured mentorship she has received as a woman, and she encourages others to seek out mentors within and outside of their organization.
Joanna, who is highly skilled in data applications for health research, showcased the importance of context when working with data. As the expert in molecular genetics, she supports all roles in data management, from curation to harmonization of multidimensional data. She also discussed the topic of data governance and privacy concerns when working with health data.
Vanessa spoke to a common question from participants: whether a PhD degree is required to work with big data. As iterated by her fellow panelists, there are many roles associated with big data. Many data scientists and other important roles require strong programming skills and knowledge in statistics but do not necessarily require a PhD degree. She encouraged our participants to understand which aspect of big data they want to work in before pursuing higher education. Specifically, she described that her own passion in machine learning and the model-building aspect of big data drove her to complete her higher education.
The event ended with a bustling networking and social time amongst the group. We received overwhelmingly positive feedback from both our panel speakers and participants. People enjoyed the comfortable and intimate environment and eagerly requested a second meetup. A shout-out to our organizers, Sandra Sousa, Lynn Yen, Emma Jones, Renita Sudirga and Sam Power for making this event a huge success!
The Toronto chapter is currently organizing its second meetup, where we will again strive to connect like-minded data professionals in a welcoming and engaging environment. Our goal is to grow, elevate and nurture female talent in the big data and analytics space through knowledge-sharing and community participation. If you are interested in participating, speaking or sponsoring us, please contact us through our meetup page!