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Overture

Overview

Overture Maps Foundation is an open data project steered by Amazon, Meta, Microsoft, and TomTom that aggregates map data from multiple sources and shares locations of points of interest. It aims to provide a comprehensive, open-source, global mapping platform that includes address data among various other geographical and location-based information, enhancing the detail and usability of open mapping data.

Key Attributes

Geographic CoverageUnited States
Entity LevelAddress, Point of Interest
Release FrequencyRoughly twice a quarter, though a regular release schedule has not been established

Notes

Each address record includes latitude and longitude coordinates for geolocation. These coordinates can be combined with the geospatial boundaries included in the geography_characteristics table. Geospatial boundaries are provided as GeoJSON and WKT polygons and are represented as coordinates. These geospatial boundaries are also referred to as ”shapefiles”, “geographic boundaries,” “bounding coordinates,” and “geographic area coordinates.”

Each POI includes the name, location, category or type of place or business, and a POI_ID unique identifier. POIs can be mapped back to addresses using the relationships table.

Address Normalization: In the us_addresses table, Cybersyn normalizes the street names, city, state, and zip codes for each address line in the dataset using our geography_index table to create consistency across city names (e.g., “Saint Paul, MN” vs. “St. Paul, MN”) and to verify accuracy. Street abbreviations are also standardized in the data (e.g., “Rd” -> “Road”).

Zip codes are determined using the address coordinates in combination with geospatial data from the US Census Bureau and are validated using data from the US Postal Service (USPS).

Point of Interest to Address Mapping: Note that more than one point of interest can map to a single address. For example, a fast food restaurant might share a location with a gas station or numerous doctors might have their own practices at a single address.

Cybersyn Products

Tables above are available in the following Cybersyn data products:

Sample Queries

Find the nearest competitor to a given merchant

Find the closest Lowe’s to any given Home Depot location

WITH joined_data AS (
SELECT poi.poi_id, poi.poi_name, addr.longitude, addr.latitude,
addr.number, addr.street_directional_prefix, addr.street,
addr.street_type, addr.street_directional_suffix,
addr.unit, addr.city, addr.state, addr.zip
FROM cybersyn.point_of_interest_index AS poi
JOIN cybersyn.point_of_interest_addresses_relationships AS map
ON (poi.poi_id = map.poi_id)
JOIN cybersyn.us_addresses AS addr
ON (map.address_id = addr.address_id)
)
SELECT *,
ST_DISTANCE(
ST_MAKEPOINT(home_depot.longitude, home_depot.latitude),
ST_MAKEPOINT(lowes.longitude, lowes.latitude)
) / 1609 AS distance_miles
FROM joined_data AS home_depot
JOIN joined_data AS lowes
WHERE home_depot.poi_name = 'The Home Depot'
AND lowes.poi_name = 'Lowe''s Home Improvement'
QUALIFY ROW_NUMBER() OVER (PARTITION BY home_depot.poi_id ORDER BY distance_miles NULLS LAST) = 1;

Query all POIs of a specific type (e.g., coffee shop) within a given ZIP code

Generate a list of all coffee shops in a given ZIP code along with their addresses

SELECT
poi.poi_name,
poi.category_main,
poi.category_alternate,
addr.number,
addr.street,
addr.street_directional_prefix,
addr.street,
addr.street_type,
addr.street_directional_suffix,
addr.unit,
addr.city,
addr.state,
addr.zip
FROM cybersyn.point_of_interest_index AS poi
JOIN cybersyn.point_of_interest_addresses_relationships AS map
ON (poi.poi_id = map.poi_id)
JOIN cybersyn.us_addresses AS addr
ON (map.address_id = addr.address_id)
WHERE addr.zip = '10003'
AND poi.category_main = 'Coffee Shop';

Disclaimers

The data in this product is sourced from Overture Maps Foundation.

Cybersyn is not endorsed by or affiliated with any of these providers. Contact snowflake-public-data@snowflake.com for questions.