2021-04-22, 14:30–15:00, Track 2
behind the scene of geo-data challenges in Moovit.
Location data is everywhere, in multiple formats and different environments.
We use python as cross-platform programming to work with our location data in many ways.
Python allows us to read, edit, and analyze location data on one hand and visualize the data, on the other hand. the data process and the visualization process can be in GIS software, Jupyter notebooks, or by standalone Python script.
In this talk, I will discuss some Geodata challenges in the operations side of Moovit.
Moovit, an Intel company, is helping to create cleaner, safer cities by guiding people in getting around town using any mode of transport. Today, Moovit serves over 950 million users in 3,400 cities across 112 countries and is the creator of the #1 urban mobility app.
Our Transit Data Repository contains millions of data points, including Real-Time arrivals and Service Alerts from more than 7500 transit operators around the world.
The data comes from multiple sources, is stored in multiple environments, and several formats. Python helps us create cross-platform processes to analyze, and visualize the data. especially for Geodata, we use Python to integrate data in QGIS for GIS experts and to create flexible reports using Jupyter notebooks for no geo experts.