Making Data Science Accessible at Scale

Despite great strides in the generation, collection, and processing of data at scale, data science is still extremely inconvenient for the vast majority of the population. The driving goal of our research is to make it easy for individuals and teams — regardless of programming or analysis expertise — manage, analyze, make sense of, and draw insights from large datasets.

In my talk, I will describe a suite of tools that we’ve been building to empower everyone to perform data science more efficiently and effortlessly, including DataSpread, a “big data” spreadsheet tool that combines the benefits of spreadsheets and databases, Zenvisage, a visual exploration tool that accelerates the discovery of trends or patterns, and Modin, a scalable dataframe system that provides the ease-of-use of Pandas, while ensuring interactivity on large datasets. Our tools have been developed in collaboration with experts in neuroscience, battery science, genomics, astrophysics, marketing analytics, and ad analytics.

Attendees will learn about some of the key technical challenges underlying the development of these tools, and how we addressed them, drawing from ideas in databases and human-computer interaction. I will finally outline a future research agenda for tool development to empower everyone to tap into the hidden potential in their datasets at scale.