
Point-of-Interest (POI) Data | Global Coverage | 250M Business Listings Data with Custom On-Demand Attributes
# | LocationID |
name |
website |
BrandID |
closedSignal |
claimed |
rating |
reviewsCount |
numberOfPictures |
photoUrl |
phone |
addressParts |
formatted_address |
parsed_address |
country |
postcode |
geometry_viewport_northeast_lng |
geometry_viewport_southwest_lat |
geometry_viewport_southwest_lng |
geometry_location_lat |
geometry_location_lng |
types |
lat |
lng |
category |
specialty |
workHours |
admin_boundary3 |
admin_boundary2 |
admin_boundary1 |
keyword |
tier1_naics_code |
tier1_naics_category |
tier2_naics_code |
tier2_naics_category |
tier3_naics_code |
tier3_naics_category |
tier4_naics_code |
tier4_naics_category |
tier5_naics_code |
tier5_naics_category |
sic_code |
sic_code_description |
calculated_geo_hash_8 |
building_id |
building_type |
building_name |
shape_type |
shape_polygon |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx |
2 | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
3 | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx |
4 | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx |
5 | 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 | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx |
6 | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx |
7 | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx |
8 | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx |
9 | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx |
10 | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx |
... | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx |
# | LocationID |
name |
website |
BrandID |
claimed |
rating |
reviewsCount |
numberOfPictures |
s3_imageUrl |
phone |
addressParts |
formatted_address |
geometry_location_type |
geometry_viewport_northeast_lat |
geometry_viewport_northeast_lng |
geometry_viewport_southwest_lat |
geometry_viewport_southwest_lng |
geometry_location_lat |
geometry_location_lng |
types |
streetAddress |
postalCode |
lat |
lng |
category |
specialty |
workHours |
admin_boundary3 |
admin_boundary2 |
admin_boundary1 |
country_code |
T4_NAICS_Code |
T4_Category |
calculated_geo_hash_8 |
building_id |
building_type |
building_name |
shape_type |
shape_polygon |
reference naics context |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
2 | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx |
3 | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
4 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx |
5 | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx |
6 | 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 | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx |
7 | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx |
8 | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx |
9 | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx |
10 | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx |
... | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
LocationID
|
String | 3808befd899cbb89e0d06cec4a2093fa | |
name
|
String | centralwOrld | |
website
|
String | https://www.centralworld.co.th/ | |
BrandID
|
String | 230cfd4264aaa7cb36112a1cb9c6c6dd | |
closedSignal
|
String | ||
claimed
|
String | t | |
rating
|
String | 4.5 | |
reviewsCount
|
String | 67178 | |
numberOfPictures
|
String | 290241 | |
photoUrl
|
String | https://lh5.googleusercontent.com/p/AF1QipNwY21VPOxVrJkSA... | |
phone
|
String | ||
addressParts
|
String | 999/9 Rama I Rd Pathum Wan Bangkok 10330 Thailand | |
formatted_address
|
String | ?????? ??????????????????????? (?????????????????? 4 4/5 ... | |
parsed_address
|
String | house: ?????? ??????????????????????? ?????????????????? ... | |
country
|
String | thailand | |
postcode
|
String | 10330 | |
geometry_viewport_northeast_lng
|
Float | 100.5404471 | |
geometry_viewport_southwest_lat
|
Float | 13.74512932 | |
geometry_viewport_southwest_lng
|
Float | 100.5377491 | |
geometry_location_lat
|
Float | 13.7464783 | |
geometry_location_lng
|
Float | 100.5390981 | |
types
|
String | street_address | |
lat
|
Float | 13.7465337 | |
lng
|
Float | 100.5391488 | |
category
|
String | Shopping mall | |
specialty
|
String | Shopping mall | |
workHours
|
String | [Tuesday 10 AM10 PM, Wednesday 10 AM10 PM, Thursday 10 ... | |
admin_boundary3
|
String | ||
admin_boundary2
|
String | ||
admin_boundary1
|
String | Krung Thep Maha Nakhon | |
keyword
|
String | Lotteria, Bangkok (TH) | |
tier1_naics_code
|
String | 53 | |
tier1_naics_category
|
String | Real Estate and Rental and Leasing | |
tier2_naics_code
|
String | 531 | |
tier2_naics_category
|
String | Real Estate | |
tier3_naics_code
|
String | 5311 | |
tier3_naics_category
|
String | Lessors of Real Estate | |
tier4_naics_code
|
String | 53112 | |
tier4_naics_category
|
String | Lessors of Nonresidential Buildings (except Miniwarehouses) | |
tier5_naics_code
|
String | 531120 | |
tier5_naics_category
|
String | Lessors of Nonresidential Buildings (except Miniwarehouses) | |
sic_code
|
String | 6512 | |
sic_code_description
|
String | Operators of Nonresidential Buildings | |
calculated_geo_hash_8
|
String | w4rqpy6r | |
building_id
|
String | way_157482067 | |
building_type
|
String | ||
building_name
|
String | ?????????????? | |
shape_type
|
String | polygon | |
shape_polygon
|
String | POLYGON ((100.5388798 13.7450505, 100.5396804 13.7449276,... |
Attribute | Type | Example | Mapping |
---|---|---|---|
LocationID
|
String | 1f4cd8c930416e8aa07f7cbdb6c4564c | |
name
|
String | Fromagerie Crčmerie Frescolet Pigalle | |
website
|
String | http://www.frescolet.fr/ | |
BrandID
|
String | 9168b8096d66e39a6e5438461caa3437 | |
claimed
|
String | t | |
rating
|
String | 4.8 | |
reviewsCount
|
String | 113 | |
numberOfPictures
|
String | 6 | |
s3_imageUrl
|
String | https://us-west-2-prod-4devs.s3.us-west-2.amazonaws.com/A... | |
phone
|
String | ||
addressParts
|
String | 42 Rue Jean-Baptiste Pigalle 75009 Paris France | |
formatted_address
|
String | 42 Rue Jean-Baptiste Pigalle, 75009 Paris, France | |
geometry_location_type
|
String | ROOFTOP | |
geometry_viewport_northeast_lat
|
Float | 48.88136298 | |
geometry_viewport_northeast_lng
|
Float | 2.33603208 | |
geometry_viewport_southwest_lat
|
Float | 48.87866502 | |
geometry_viewport_southwest_lng
|
Float | 2.33333412 | |
geometry_location_lat
|
Float | 48.880014 | |
geometry_location_lng
|
Float | 2.3346831 | |
types
|
String | establishment, food, point_of_interest, store | |
streetAddress
|
String | 42 Rue Jean-Baptiste Pigalle | |
postalCode
|
String | 75009 | |
lat
|
Float | 48.880014 | |
lng
|
Float | 2.3346831 | |
category
|
String | Cheese shop | |
specialty
|
String | Cheese shop, Dairy store | |
workHours
|
String | [Monday 3:308 PM, Tuesday 9:30 AM8 PM, Wednesday 9:30 A... | |
admin_boundary3
|
String | ||
admin_boundary2
|
String | Département de Paris | |
admin_boundary1
|
String | Île-de-France | |
country_code
|
String | FR | |
T4_NAICS_Code
|
String | 445299 | |
T4_Category
|
String | All Other Specialty Food Stores | |
calculated_geo_hash_8
|
String | u09wj4k4 | |
building_id
|
String | way_69562879 | |
building_type
|
String | ||
building_name
|
String | ||
shape_type
|
String | polygon | |
shape_polygon
|
String | POLYGON ((2.3345769 48.8800387, 2.3346835 48.8799702, 2.3... | |
reference naics context
|
String | 311511 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Custom value | Brand Name | |
String | 59114 | Postal Code | |
Category
|
Fast Food Restaurants | ||
Float | 35.8506174 | Latitude | |
Float | 14.5127686 | Longitude | |
String | IPv4 Address | ||
String | Address | ||
Building_name
|
Pesona square | ||
Is_independent
|
True | ||
Level_no
|
15 | ||
Unit_no
|
03-21 | ||
String | depot pinilih | Location Name | |
String | Jakarta | City Name | |
Region
|
Central Java | ||
Text | [{'day': 'Mon', 'from': '08:00Am', 'to': '10:00Pm'} | POI Opening Hours | |
Is_open_for_business
|
True | ||
Updated-At
|
1636106079789 | ||
Operator_name
|
Singtel | ||
String | ID | Country Code Alpha-2 | |
Position
|
Inside the building | ||
Geohash
|
qqycw | ||
Photos
|
3effd6f1-004f-4ea0-8008-e20e378f2ade_20211103_07272159153... | ||
Verify_location
|
[Decimal('111.0386646'), Decimal('-6.7555302')] | ||
Horizontal accoracy
|
'horizontal_accuracy': Decimal('27.867'), 'provider': 'fu... | ||
Custom Attribute
|
custom value |
Description
Country Coverage
Volume
250 | Million POI |
Pricing
License | Starts at |
---|---|
One-off purchase | Available |
Monthly License | Available |
Yearly License | Available |
Usage-based | Not available |
Suitable Company Sizes
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes?
Quadrant’s POI Data-as-a-Service provides geospatial applications a contextual layer of comprehensive and actionable information on landmarks, key features, business areas, and custom metadata attributes.
What is Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes used for?
This product has 5 key use cases. Quadrant recommends using the data for Location Intelligence, Location Analytics, Location Verification, Point of Interest (POI) Mapping, and Point of Interest (POI) Marketing. Global businesses and organizations buy Location Data from Quadrant to fuel their analytics and enrichment.
Who can use Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Location Data. Get in touch with Quadrant to see what their data can do for your business and find out which integrations they provide.
Which countries does Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes cover?
This product includes data covering 250 countries like USA, China, Japan, Germany, and India. Quadrant is headquartered in Singapore.
How much does Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes cost?
Pricing information for Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes is available by getting in contact with Quadrant. Connect with Quadrant to get a quote and arrange custom pricing models based on your data requirements.
How can I get Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes?
Businesses can buy Location Data from Quadrant and get the data via S3 Bucket and Email. Depending on your data requirements and subscription budget, Quadrant can deliver this product in .json, .csv, and .xls format.
What is the data quality of Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes?
You can compare and assess the data quality of Quadrant using Datarade’s data marketplace. Quadrant appears on selected Datarade top lists ranking the best data providers, including Best Data Providers For Location-Based Marketing.
What are similar products to Point-of-Interest (POI) Data Global Coverage 250M Business Listings Data with Custom On-Demand Attributes?
This product has 3 related products. These alternatives include Location Data Global Location Data on 56M+ POI SafeGraph Places, Global Point-of-Interest Data POI, Geospatial, Sentiment (Reviews), Footfall, Business Listings & Store Location 251 Millions+ POI Data Mapped, and Point of Interest (POI) Data Worldwide 82M Dataset Commercial POIs. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.