Asset of CARTO's Data Catalog.

Data Observatory

Augment your internal data & broaden your analysis with the latest & greatest in third party location data, reducing the time spent gathering, evaluating & cleaning data.

The Data Observatory in numbers

CARTO's Data Observatory brings together thousands of open and premium datasets enabling a wide range of organizations to take the pain out of sourcing spatial data.

Working with spatial data

  • Finding the location data I need can take weeks as there are too many providers offering similar data and it’s difficult to assess quality

  • Licensing can also be a long and tedious process: I’ll have to negotiate terms with every single data provider

  • Enriching my data will be hard as I’ll need to deal with different formats and support geographies

How the Data Observatory can help

  • Simple access to public and premium data from vetted sources

  • Faster licensing process thanks to existing agreements with leading data providers

  • Easy enrichment with data already presented in standardized formats

DATA AVAILABLE

The Data Observatory allows you to use the highest quality location data out there from across the globe, such
 as human mobility, financial, and POI data. We partner with market-leaders to bring together accurate, ready-to-use datasets to reduce your time
 to insight, whatever your use case.

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DATA ANALYSIS EXAMPLES

CPG Firms

CPG firms select pop up sites by using CARTO’s POI data to identify where certain target segments may also visit, allowing them to reduce the risk of a poor site decision. By looking at age, gender, rental price data, and transport accessibility, CPG firms can identify ideal locations based on the target audience of the product potentially being sold at the pop-up site.

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DATA ANALYSIS EXAMPLES

Local Governments

Local governments (such as New York City) rely on GPS data to gain insights that measure the risk of overcrowding by station. In this example, NYC was able to blend MTA turnstile data with Safegraph’s human mobility data to identify which subway stations were at higher risk during the COVID-19 outbreak.

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Want to try out some data?