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Workflows examples

How to use these examples
The CARTO team has designed this collection of Workflows examples with a hands-on approach to empower users and ease the Workflows learning curve. 
These examples showcase a wide range of scenarios and applications: from simple building blocks for your geospatial analysis to more complex, industry-specific workflows tailored to facilitate running specific geospatial use-cases.
Making use of these examples is very easy. Just download them and import into your CARTO account. Each example will import the necessary data upon recreation of the Workflow in your account. Once the workflow is ready, you will be able to modify it, replacing the data sources and re-configuring the different nodes so it can be useful for your specific use-case.
Catalog of workflow examples
Data Preparation
​Joining different datasets by a common column​
​Join two datasets and group by a property ​
​Union of two data sources sharing the same schema​
​Filter rows using a custom geography​
​Generate a new column from a multi-column formula​
​Normalize a variable to an index between 0 to 1 ​
​Rank and limit a table​
​Filter key columns and calculate an additional column​
Data Enrichment
​Enrich a set of buffers using Quadbin indexes​
​Enrich trade areas using H3 indexes​
​Enrich Point data with a custom source​
​Enrich Polygon data with a custom source​
​Enrich Grid data with a custom source​
Spatial Indexes
​Polyfill a set of polygons with H3 indexes​
​Aggregate point data into a Quadbin grid​
​Aggregate point data into an H3 grid​
​Use H3 K-rings to define areas of influence​
Spatial Analysis
​Find clusters of customers with K-Means algorithm​
​Find points that lie within a set of polygons and add properties​
​Aggregate point data into polygons​
​Generate Voronoi polygons from a set of points​
​Find the K-nearest neighbors to a set of points​
​Find nearest points and create routes by car​
​Custom SQL Select using 2 inputs​
Generating new spatial data
​Draw Custom Geographies​
​Create routes from origin/destination dataset​
​Geocode street addresses into point geometries​
​Generate points out of Latitude and Longitude columns​
​Generate isochrones from point data​
Statistics
​Identify hotspots of specific types of points of interest​
​Space-time hotspot analysis​
​Computing the spatial auto-correlation of point of interest locations​
​Applying Geographical Weighted Regression (GWR) to model the local spatial relationships in your data​
Retail and CPG
​Estimate population around top performant retail stores​
​Find closest two stores from customers' home locations​
​Identify and analyze the commercial hotspots in an area​
Telco
​Estimate population covered by a telecommunications cell network​
OOH Advertising
​Identify the best billboards to target a specific audience​
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Workflows best practices

Data Preparation

Last modified 1mo ago