Every day, Uber manages billions of GPS locations. All over the world, Uber is coordinating dropoffs, pickups, and deliveries in real-time—across a literally global field of infrastructures and on-the-ground realities. Our constant goal is to continue to improve the experience for Uber’s users. The raw geospatial data that is accumulated through our everyday operations forms an incredibly rich set of learning material to make Uber even better.
However, raw data by itself is not useful—endless scattered nodes stretching across the globe. It is only when we view that data in context that it begins to paint a picture.
Data platformJoin our team
Team members / roles
Team members / roles
- Nicolas Garcia Belmonte - Head of Data Visualization
- Shaojing Li - Data Visualization Specialist
- Shan He - Data Visualization Specialist
- Ib Green - Data Visualization Specialist
- Xiaoji Chen - Data Visualization Specialist
- Yang Wang - Data Visualization Specialist
- Balthazar Gronon - Data Visualization Specialist
In early 2015, we started an official data visualization team at Uber. The idea behind it: deliver intelligence through crafting visual data analysis tools.
DeckGL is the culmination of that team’s work: a WebGL-powered framework for visual exploratory data analysis of large datasets.
From topographic wind maps to population migration studies, DeckGL’s versatility makes it an asset in rendering a broad scope of visualizations.
Without visualization, data is just so much noise, not much signal. Data visualization is essentially the art of teaching the data how to be meaningful—in effect, to teach data how to best teach us.
Data visualization serves two main purposes: explanation and exploration. These functions often overlap and complement each other, but it’s useful to think of them as fundamentally different.
Data visualization shapes our product
We invest heavily in experimental tools and frameworks because we believe in their potential to enrich our users’ lives. We’ve already seen DeckGL inform product decisions at Uber that helped to make drivers and riders alike happier.
Data visualizations help us improve the pickup experience—particularly in complex environments such as airports.
We can better visualize models for UberEATS delivery time in order to give users a more accurate ETA.
And in a crowded city, we can capture the constant, dynamic change that makes it easier to see the best places for cars to go at any given time.
High performance computations
DeckGL offers high-performance rendering of large data sets (millions of points or vertices), including features like on-the-fly aggregation and visual exploration, based on latest WebGL technologies.
A layered approach to data visualization
Visualize and combine multiple layers to gain new perspectives on your data.
Designed to process and depict multiple types of geometry features defined in the GeoJSON format.
Using government-supplied open data to render hundreds of thousands of discrete data points.
Plays well with others
React and Mapbox friendly, enhancing these open source frameworks with advanced features for visual exploration and storytelling.
See data like never before
From data designers to engineers, we empower creative technologists across the board to take advantage of DeckGL’s versatile suite of tools to realize the potential of their data.
With DeckGL, we knew that we had created an incredibly powerful tool for data visualization, one that went far beyond Uber’s own use cases. As creators and designers, we wanted to share this tool with the world, to see what other teams and individuals could do with it.
As other designers and engineers continue to use DeckGL to explain and explore, we learn how to make it even better. This cumulative progress is at the heart of the open source ideology. We are thrilled to make our own modest contribution. That’s why we hope that you will try it out—and we can’t wait to see what you’ll do next.