Location Data | Dataset: 164M+ Locations Worldwide
| # | UniqueID |
CompanyName |
TradeName |
Address1 |
Address2 |
PostCode |
City |
CityCode |
Locality |
LocalityCode |
Province |
ProvinceCode |
Region |
RegionCode |
Country |
CountryCode |
Language |
PhoneOrMobile |
Phone |
Fax |
Mobile |
Email |
Website |
InfobelCode |
InfobelLabel |
PrimaryLocalActivityCode |
LocalActivityTypeCode |
YearStarted |
NumberOfFamilyMembers |
EmployeesHere |
EmployeesHereReliabilityCode |
EmployeesHereReliabilityCodeDescription |
EmployeesTotal |
EmployeesTotalReliabilityCode |
EmployeesTotalReliabilityCodeDescription |
LegalStatusCode |
LegalStatusCodeDescription |
StatusCode |
StatusCodeDescription |
SalesVolumeLocal |
CurrencyCode |
SalesVolumeDollars |
SalesVolumeEuros |
SalesVolumeReliabilityCode |
SalesVolumeReliabilityCodeDescription |
GenericOpeningHours |
Longitude |
Latitude |
GeoLevel |
GeoLevelDescription |
BuildingName |
BuildingType |
BuildingGeom |
BuildingArea |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx |
| 2 | 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 | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx |
| 3 | 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 | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx |
| 4 | 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 | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx |
| 5 | 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 | 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 |
| 6 | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | 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 | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx |
| 7 | 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 | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx |
| 8 | 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 |
| 9 | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | 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 |
| 10 | 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 | xxxxxxxx |
| ... | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxx | xxxxxxxx | xxxxxx |
Volume
3.2K
Business sectors
Avail. Formats
.bin, .json, and .xml
File
Coverage
250
Countries
History
8
years
Data Dictionary
[Sample] Location Data Sample Global.csv
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
UniqueID
|
Integer | 32489898 | |
|
CompanyName
|
String | Amy & Bryan Smith | |
|
TradeName
|
|||
|
Address1
|
String | 3685 Abrazite Way | |
|
Address2
|
|||
|
PostCode
|
Integer | 30040 | |
|
City
|
String | Cumming | |
|
CityCode
|
String | USGA11790828_4514097 | |
|
Locality
|
|||
|
LocalityCode
|
|||
|
Province
|
String | Forsyth | |
|
ProvinceCode
|
String | USGA117 | |
|
Region
|
String | Georgia | |
|
RegionCode
|
String | USGA | |
|
Country
|
String | USA | |
|
CountryCode
|
String | US | |
|
Language
|
String | ENG | |
|
PhoneOrMobile
|
|||
|
Phone
 |
|||
|
Fax
|
|||
|
Mobile
|
|||
|
Email
|
|||
|
Website
|
|||
|
InfobelCode
|
|||
|
InfobelLabel
|
|||
|
PrimaryLocalActivityCode
|
|||
|
LocalActivityTypeCode
|
|||
|
YearStarted
|
Integer | 2011 | |
|
NumberOfFamilyMembers
|
|||
|
EmployeesHere
|
Integer | 2 | |
|
EmployeesHereReliabilityCode
|
Integer | 3 | |
|
EmployeesHereReliabilityCodeDescription
|
String | Modeled | |
|
EmployeesTotal
|
Integer | 2 | |
|
EmployeesTotalReliabilityCode
|
Integer | 3 | |
|
EmployeesTotalReliabilityCodeDescription
|
String | Modeled | |
|
LegalStatusCode
|
|||
|
LegalStatusCodeDescription
|
|||
|
StatusCode
|
Integer | 0 | |
|
StatusCodeDescription
|
String | SingleLocation | |
|
SalesVolumeLocal
|
Integer | 92254 | |
|
CurrencyCode
|
String | USD | |
|
SalesVolumeDollars
|
Integer | 92254 | |
|
SalesVolumeEuros
|
Integer | 87237 | |
|
SalesVolumeReliabilityCode
|
Integer | 3 | |
|
SalesVolumeReliabilityCodeDescription
|
String | Modeled | |
|
GenericOpeningHours
|
|||
|
Longitude
|
Float | -84.22818649999999 | |
|
Latitude
|
Float | 34.209387 | |
|
GeoLevel
|
Integer | 5 | |
|
GeoLevelDescription
|
String | RoofTop Derived | |
|
BuildingName
|
|||
|
BuildingType
|
String | building | |
|
BuildingGeom
|
String | MULTIPOLYGON (((-84.228126 34.209297, -84.22808 34.209449... | |
|
BuildingArea
|
Integer | 244 |
Description
Access 164M+ verified locations across 220+ countries, empowering smarter decision-making with precise, customizable Location Data.
Leverage advanced location data from high-quality geospatial data covering patterns, behaviours, and trends across diverse industries. With accurate insights from multiple sources, our solutions empower businesses in retail, logistics, real estate, finance, and urban planning to optimize operations, enhance decision-making, and drive strategic growth.
Key use cases where Location Data has helped businesses :
1. Optimize Logistics & Route Planning : Streamline delivery routes, reduce transit times, and enhance operational efficiency with precise location intelligence.
2. Enhance Market Positioning & Competitor Insights : Identify high-traffic zones, analyse competitor locations, and fine-tune business strategies to maximize market presence.
3. Transform Navigation & EV Infrastructure : Power navigation systems, real-time travel recommendations, and EV charging station mapping for seamless location-based services.
4. Enhance Urban & Retail Site Selection : Identify optimal locations for stores, warehouses, and infrastructure investments with in-depth spatial data and demographic insights.
5. Strengthen Spatial Analysis & Risk Management : Leverage advanced geospatial insights for disaster preparedness, public health initiatives, and land-use optimization.
Country Coverage
Africa
(58)
Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo
Congo (Democratic Republic of the)
Côte d'Ivoire
Djibouti
Egypt
Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mayotte
Morocco
Mozambique
Namibia
Niger
Nigeria
Rwanda
Réunion
Saint Helena, Ascension and Tristan da Cunha
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Swaziland
Tanzania, United Republic of
Togo
Tunisia
Uganda
Western Sahara
Zambia
Zimbabwe
Asia
(51)
Afghanistan
Armenia
Azerbaijan
Bahrain
Bangladesh
Bhutan
Brunei Darussalam
Cambodia
China
Cyprus
Georgia
Hong Kong
India
Indonesia
Iran (Islamic Republic of)
Iraq
Israel
Japan
Jordan
Kazakhstan
Korea (Democratic People's Republic of)
Korea (Republic of)
Kuwait
Kyrgyzstan
Lao People's Democratic Republic
Lebanon
Macao
Malaysia
Maldives
Mongolia
Myanmar
Nepal
Oman
Pakistan
Palestine, State of
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Syrian Arab Republic
Taiwan
Tajikistan
Thailand
Timor-Leste
Turkey
Turkmenistan
United Arab Emirates
Uzbekistan
Vietnam
Yemen
Europe
(52)
Albania
Andorra
Austria
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Germany
Gibraltar
Greece
Guernsey
Holy See
Hungary
Iceland
Ireland
Isle of Man
Italy
Jersey
Kosovo
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia (the former Yugoslav Republic of)
Malta
Moldova (Republic of)
Monaco
Montenegro
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovakia
Slovenia
Spain
Svalbard and Jan Mayen
Sweden
Switzerland
Ukraine
United Kingdom
Åland Islands
North America
(13)
Belize
Bermuda
Canada
Costa Rica
El Salvador
Greenland
Guatemala
Honduras
Mexico
Nicaragua
Panama
Saint Pierre and Miquelon
United States of America
Oceania
(25)
American Samoa
Australia
Cook Islands
Fiji
French Polynesia
Guam
Kiribati
Marshall Islands
Micronesia (Federated States of)
Nauru
New Caledonia
New Zealand
Niue
Norfolk Island
Northern Mariana Islands
Palau
Papua New Guinea
Pitcairn
Samoa
Solomon Islands
Tokelau
Tonga
Tuvalu
Vanuatu
Wallis and Futuna
Other
(9)
Antarctica
Bouvet Island
British Indian Ocean Territory
Christmas Island
Cocos (Keeling) Islands
French Southern Territories
Heard Island and McDonald Islands
South Georgia and the South Sandwich Islands
United States Minor Outlying Islands
South America
(42)
Anguilla
Antigua and Barbuda
Argentina
Aruba
Bahamas
Barbados
Bolivia (Plurinational State of)
Bonaire, Sint Eustatius and Saba
Brazil
Cayman Islands
Chile
Colombia
Cuba
Curaçao
Dominica
Dominican Republic
Ecuador
Falkland Islands (Malvinas)
French Guiana
Grenada
Guadeloupe
Guyana
Haiti
Jamaica
Martinique
Montserrat
Paraguay
Peru
Puerto Rico
Saint Barthélemy
Saint Kitts and Nevis
Saint Lucia
Saint Martin (French part)
Saint Vincent and the Grenadines
Sint Maarten (Dutch part)
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela (Bolivarian Republic of)
Virgin Islands (British)
Virgin Islands (U.S.)
History
8 years of historical data
Volume
| 220 | Countries |
| 164 | M+ companies |
| 3,200 | Business sectors |
| 50 | + Data attributes |
Pricing
InfobelPRO has not published pricing information for this product yet.
You can request detailed pricing information below.
Suitable Company Sizes
Small Business
Medium-sized Business
Enterprise
Delivery
Methods
S3 Bucket
SFTP
Email
UI Export
REST API
SOAP API
Streaming API
Feed API
Frequency
daily
weekly
monthly
quarterly
Format
.bin
.json
.xml
.csv
.xls
.sql
.txt
Use Cases
Categories
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250 countries covered
8 years of historical data
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Frequently asked questions
What is Location Data Dataset: 164M+ Locations Worldwide?
Access 164M+ verified locations across 220+ countries, empowering smarter decision-making with precise, customizable Location Data.
What is Location Data Dataset: 164M+ Locations Worldwide used for?
This product has 5 key use cases. InfobelPRO recommends using the data for Location Analytics, Risk Management, Retail Intelligence, Location Planning, and Navigation. Global businesses and organizations buy Location Data from InfobelPRO to fuel their analytics and enrichment.
Who can use Location Data Dataset: 164M+ Locations Worldwide?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Location Data. Get in touch with InfobelPRO to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Location Data Dataset: 164M+ Locations Worldwide go?
This product has 8 years of historical coverage. It can be delivered on a daily, weekly, monthly, and quarterly basis.
Which countries does Location Data Dataset: 164M+ Locations Worldwide cover?
This product includes data covering 250 countries like USA, China, Japan, Germany, and India. InfobelPRO is headquartered in Belgium.
How much does Location Data Dataset: 164M+ Locations Worldwide cost?
Pricing information for Location Data Dataset: 164M+ Locations Worldwide is available by getting in contact with InfobelPRO. Connect with InfobelPRO to get a quote and arrange custom pricing models based on your data requirements.
How can I get Location Data Dataset: 164M+ Locations Worldwide?
Businesses can buy Location Data from InfobelPRO and get the data via S3 Bucket, SFTP, Email, UI Export, REST API, SOAP API, Streaming API, and Feed API. Depending on your data requirements and subscription budget, InfobelPRO can deliver this product in .bin, .json, .xml, .csv, .xls, .sql, and .txt format.
What is the data quality of Location Data Dataset: 164M+ Locations Worldwide?
You can compare and assess the data quality of InfobelPRO using Datarade’s data marketplace. InfobelPRO has received 4 reviews from clients. InfobelPRO appears on selected Datarade top lists ranking the best data providers, including Who’s New on Datarade? January Edition.
What are similar products to Location Data Dataset: 164M+ Locations Worldwide?
This product has 3 related products. These alternatives include Location Intelligence Data 164M+ Locations, The Data Appeal Global Business Location Data 200 Million+ POI Data Mapped Coverage from 2019 API, Dataset, and Location Data Global Location Data on 56M+ POI SafeGraph Places. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.
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