US Restaurant POI dataset with metadata
# | main_category |
second_category |
adr |
prov |
source_url |
crawl_time |
|||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx |
2 | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx |
3 | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
4 | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx |
5 | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx |
6 | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx |
7 | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx |
8 | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
9 | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx |
10 | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx |
... | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Burger King | POI Name | |
String | Burger King | Brand Name | |
Integer | 15172347013 | POI Telephone | |
main_category
|
String | Restaurant | |
second_category
|
String | Fast food restaurant | |
Integer | 1951878493552 | Location ID | |
Integer | 164280 | Area ID | |
Integer | 195187849 | Small Area ID | |
Float | 42.741559 | Latitude | |
Float | -84.660402 | Longitude | |
adr
|
String | 7416 W Saginaw Hwy | |
String | Lansing | City Name | |
String | Delta Center | Neighborhood Name | |
prov
|
String | MI | |
Integer | 48917 | Postal Code | |
String | USA | Country Name | |
String | Address | ||
source_url
|
String | burgerking.com/store-locator/store/restaurant_3515 | |
String | Email Address | ||
String | Mo-Sa 06:00-22:00; Su 07:00-22:00; Su 07:00-24:00 open 'd... | POI Opening Hours | |
crawl_time
|
DateTime | 2022-07-30T16:50:36+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | China Garden | POI Name | |
String | 19496539988 | POI Telephone | |
main_category
|
Chinese restaurant | ||
second_category
|
Asian restaurant | ||
String | 2094288246693 | Location ID | |
String | 176266 | Area ID | |
Integer | 209428824 | Small Area ID | |
Float | 33.68801 | Latitude | |
Float | -117.77092 | Longitude | |
adr
|
14825 Jeffrey Road | ||
String | Irvine | City Name | |
String | Downtown | Neighborhood Name | |
prov
|
CA | ||
String | 92618 | Postal Code | |
String | USA | Country Name | |
String | Address | ||
source_url
|
chinagardenirvine.com | ||
String | Email Address | ||
crawl_time
|
2021-04-09 19:46:21 | ||
String | N/A | Brand Name | |
additional_categories
|
Restaurant |
Description
Country Coverage
Volume
686,000 | records |
Pricing
License | Starts at |
---|---|
One-off purchase |
$8,900$8,010 / purchase |
Monthly License | Not available |
Yearly License |
$7,500$6,750 / year |
Usage-based |
$0.01$0.01 / per restaurant record |
Suitable Company Sizes
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is US Restaurant POI dataset with metadata?
This is a complete US restaurant POI data for USA as of October 2021 containing 686,482 active restaurants and eating places in the USA geocoded with rooftop accuracy.
What is US Restaurant POI dataset with metadata used for?
This product has 2 key use cases. Geolytica recommends using the data for Point of Interest (POI) Mapping and Point of Interest (POI) Marketing. Global businesses and organizations buy Restaurant Data from Geolytica to fuel their analytics and enrichment.
Who can use US Restaurant POI dataset with metadata?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Restaurant Data. Get in touch with Geolytica to see what their data can do for your business and find out which integrations they provide.
Which countries does US Restaurant POI dataset with metadata cover?
This product includes data covering 1 country like USA. Geolytica is headquartered in Canada.
How much does US Restaurant POI dataset with metadata cost?
Pricing for US Restaurant POI dataset with metadata starts at USD0.01 per per restaurant record. Geolytica offers a 10% discount when you buy data from them through Datarade. Connect with Geolytica to get a quote and arrange custom pricing models based on your data requirements.
How can I get US Restaurant POI dataset with metadata?
Businesses can buy Restaurant Data from Geolytica and get the data via S3 Bucket, Email, and REST API. Depending on your data requirements and subscription budget, Geolytica can deliver this product in .csv format.
What is the data quality of US Restaurant POI dataset with metadata?
You can compare and assess the data quality of Geolytica using Datarade’s data marketplace. Geolytica appears on selected Datarade top lists ranking the best data providers, including Who’s New on Datarade? .
What are similar products to US Restaurant POI dataset with metadata?
This product has 3 related products. These alternatives include Global Bar & Restaurant Data Points of Interest (POI), The Data Appeal Location Data, Point of Interest (POI) Data and Map Data API, Dataset 200 Million + POI Data Mapped Coverage from 2019, and GapMaps Premium Point of Interest (POI) Data India Point of Interest (POI) for Leading Retail Brands Monthly Tracking. You can compare the best Restaurant Data providers and products via Datarade’s data marketplace and get the right data for your use case.