James Kunstle

The lifecycle of data projects is involved. Responsibility for data, properly storing and retrieving data, scalably processing data… it can be a bit much. This talk will focus on a later-stage of the data lifecycle: serving data visualizations and analysis with sustainability in mind. About a year ago, our team had to pick which tool we wanted to use to serve data visualizations and metrics to stakeholders. We had a laundry-list of requirements, some being deal-breakers while others were nice-to-haves. Our final verdict was a project that fit specific needs for us as a data science team, but in the process of choosing, we piloted a diverse variety of other alternative projects. The framework for this talk is simple: introduce a collection of stand-out data visualization projects and discuss the pros and cons of each as we see them for a variety of use cases. All considered projects are open source. They will be introduced in ascending order of interface complexity- and perhaps descending order of customizability. For example, the first project provides the user with a UI for doing data analysis- a later project will require a Python back-end. The intended take-away of this talk is to provide attendees with a survey of projects that could serve them, and to shortcut the attendees own path toward finding a solution that works best for their team, minimizing platform-churn and saving time.