Abstract: 

Data can be communicated in a wide variety of ways, from transferring a file of raw data between parties to summarizing the key results of a dataset using a few sentences. Spanning the vast breadth of that spectrum lies Data Visualization, which can allow communicators to explain key points visually, or even allow audiences to explore the data on their own. At the heart of this talk is the notion of "explanatory" vs "exploratory" communication - If you're tasked with *explaining* a data insight, a copy of the same visuals you, the expert, used to *explore* the data will not necessarily be intuitive to your audience. In this talk, we'll break down some of the key concepts to consider when communicating data, a short list of DOs & DON'Ts, and survey a variety of techniques that current practitioners use to effectively communicate data. This talk will be heavily example-driven - communication is both an art and science and as such, sometimes the best way to improve is to observe lots of great examples.

Bio: 

Matt is Director of Data Science with over a decade of experience solving complex business problems with data, modeling and simulation. Over the past year in his tenure at project44, Matt has been scaling the data science team from a few disparate efforts to a full department of 30 team members around the globe. The data science team at project44 uses the billions of shipments that are tracked through project44’s platform to extract insights that help customers made data-driven decisions: everything from “estimated time of delivery” to “impact of the latest disruptions”. Project44’s data science team uses state-of-the-art Machine Learning techniques to capture the dynamic trends and patterns of today’s supply chain. Despite the pandemic and global nature of Matt’s team – the data scientists at project44 routinely hold “virtual whiteboarding sessions” where they brainstorm, trade ideas about statistical techniques, and also discuss their latest Netflix favorites.