Cameron Yick: Bridging the code-click gap with low code data visualization

Abstract:

When exploring data, should I chart my data in a spreadsheet, or should I learn to program using R/Python/D3? Data Visualization meetup attendees often ask when to use coding versus "no-code" (GUI, graphical user interface) tools . This question is also on the minds of HCI (human computer interaction) researchers, and anyone who has needed to visualize data at work.

On one side, click-based tools offer speed at the cost of less flexibility. On the other side, coding offers great freedom at the cost of cognitive effort. We should not have to choose one. Teams will benefit from using each approach at different stages. Low code tools bridge the gap by producing files and formats usable by tools at either end. As someone who aims to make data accessible to users from all backgrounds, and a person who can code but is limited on time, I have an interest in tools that combine the strengths of both approaches.

In this talk, I will share several of the free and open source options in this space with you. Attendees will learn about a collection of technologies that bridge the code-click gap, and show a "low floor, high ceiling" approach to choosing data visualization tools. A "low code" approach to data exploration can benefit both professionals and newcomers alike.

Bio:

Cameron Yick is a senior software engineer developing interactive data visualizations and diagrams at Datadog. He contributes to open-source data tool ecosystems including Vega, Nteract, and Datasette. He has presented on topics ranging from "code maps" to civic tech volunteering at open data and software conferences. He holds a BS in Electrical Engineering and Computer Science from Yale University. You can find him online on Twitter or his website.