Spatial Data Science
Boost your Spatial Analytics with Snowflake ML in CARTO
Discover how Snowflake ML in CARTO simplifies machine learning for spatial analytics. Easily build, train, and deploy forecasting models in your workflows.
Build A Clicks-to-Bricks Strategy Using Spatial Data Science
For online-native retailers eyeing growth and expansion, a clicks-to-bricks strategy using geospatial analytics can mitigate risk in site planning
Predicting Collisions in NYC with New Data Streams and Spatial Analysis
For traffic engineers and analysts looking to tackle major challenges, such as reducing the number of car crashes in their city, new data streams and spatial data science are critical
Using Spatial Interaction Models to Predict Behaviors
A spatial interaction model is specifically used to map and model the interactivity between various factors in distinct locations. This makes it extremely useful to understanding any data you might have with more than one location component.
Why spatial analysis is key to ending pharmacy deserts and the opioid epidemic
Learn to apply different types of spatial analysis to location data to determine whether or not community pharmacies are accessible in our latest post
Academy











Live maps with automated Workflows integrations are here
Create live, always-updated maps with CARTO by integrating Workflows and Builder. Automate geospatial analysis to visualization in one step.











Introducing User Comments: boost collaboration in your maps
Boost team collaboration with User Comments in CARTO Builder—add, track, and resolve feedback directly on your enterprise maps.











Navigate global risk with MBI CONIAS Political Risk data
Monitor and forecast global political risks with MBI CONIAS data - spatial, predictive, and ready to support smarter decisions in volatile regions.