Create Engaging Data Visualizations with Google Maps
Pop Quiz: You have a large, rich, geospatial data set you want to display on a Google map. Maybe it’s census data, election results, real estate values, sales performance or natural disaster locations. You’d like to use dynamic, data-driven symbology to present the information in an engaging way. What’s the best way to store and visualize that data?
At this point, you may be thinking that Google Maps may not be able to handle this. And until recently, I likely would have agreed. I would have recommended a platform like ArcGIS or CARTO for this kind of visualization. Several recent key developments in Google Cloud and Google Maps have changed the story, with help from a novel source: the Uber Visualization team.
deck.gl Google Maps Integration
The Uber Visualization team is doing some really exciting work building open-source frameworks that leverage cutting-edge technology for data visualization. If you’re not familiar, I encourage you to peruse the website and Uber’s GitHub to check out what they’re up to.
One of the libraries maintained by the Uber Vis team is deck.gl. deck.gl is a high-performance visualization library that leverages WebGL to render large quantities of vector data. Combined with a base map, deck.gl is a powerful new way to create engaging, beautiful maps.
*Check out the deck.gl showcase to see examples of its incredible creative styling capabilities.
One of the great things about running a Cloud SQL database is support for spatial data types directly out of the box. Both the MySQL and PostgreSQL flavors of Cloud SQL have their spatial extensions installed, which means they’re great options for storing geospatial data. At Google Next ‘19, Google announced alpha support for the SQL Server database engine in Cloud SQL. SQL Server has native support for spatial data types, so it too is a strong option.
But what if a relational database isn’t a good fit? What if you have terabytes or petabytes of data that may not be practical to store in Cloud SQL? For that, there is BigQuery GIS.
BigQuery GIS is a new set of capabilities that brings spatial data types and functions to BigQuery. BigQuery is a great solution for data warehousing and analytics, and with the addition of GIS functionality, you can use BigQuery to extract spatial intelligence from your data. These features were announced in beta at Google Next ’18, and at this year’s conference, Google announced general availability for BigQuery GIS.
*For a great example of what you can build with BigQuery GIS, check out Global Fishing Watch’s vessel map.
Together, BigQuery GIS and deck.gl form a powerful new way to create visualizations in Google Maps.
Google’s blog announcing deck.gl integration Uber Vis team's blog with more details on using deck.gl with Google Maps Google I/O 2019 "Google Maps Platform: A Deep Dive on Building for Performance and Scale" Example code on GitHub Google Next ‘19 “Making Planet Scale Geospatial Processing Possible with BigQuery GIS”