In this section we provide a set of examples that showcase how to leverage the functions of our Analytics Toolbox to unlock advanced spatial analyses in your data warehouse platform. They cover a broad range of use cases with methods for data transformations, enrichment, spatial indexing in Quadkey and H3, statistics, clustering, spatial data science methods and more.
The Analytics Toolbox can be leveraged from the SQL Query editor in Builder, your data warehouse console, or in SQL and Python Notebooks using the SQL clients provided by the different cloud platforms.
Voronoi diagrams are a very useful tool to build influence regions from a set of points and the Analytics Toolbox provides a convenient function to build them. An example application of these diagrams is the calculation of the coverage areas of a series of weather stations. In the following query we are going to calculate these influence areas in the state of New York. The result can be seen in the visualization below, where the color of each polygon indicates its area, which gives an insight on the coverage provided by the station.
Providing a good network connection between subway stations is critical to ensure an efficient mobility system in big areas. Let's imagine we need to design a well-distributed subway network to connect the stations of a brand-new subway system. A simple and effective solution to this problem is to build a Delaunay triangulation of the predefined stations, which ensures a good connection distribution.
In this example we are going to use some of the functions included in CARTO's Analytics Toolbox in order to highlight zones prone to earthquakes, using a BigQuery public dataset.