The Data Appeal | Geospatial Data | 251 Million POIs Mapped | GDPR-compliant | 5 Years of Historic Data
# | poi_id |
type |
value |
date_last_checked |
---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx |
2 | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx |
3 | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx |
4 | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx |
5 | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
6 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx |
7 | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx |
8 | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx |
9 | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx |
10 | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
... | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx |
# | poi_id |
name |
street_address |
latitude |
longitude |
industry |
category |
date_refreshed |
name_translated |
country |
state |
county |
city |
stars |
rooms |
price_class |
sentiment |
popularity |
hours_popular |
main_clusters |
most_discussed_topics |
spoken_languages |
traveler_origin |
traveler_type |
phone |
website |
brand_name |
date_first_presence |
date_closed |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | 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 | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx |
3 | 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 |
4 | 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 |
5 | 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 |
6 | xxxxxx | Xxxxx | 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 |
7 | 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 |
8 | 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 |
9 | 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 |
10 | 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 | 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 |
# | poi_id |
day_of_week |
period_time |
open_time |
close_time |
date_last_checked |
---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx |
2 | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx |
3 | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx |
4 | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx |
5 | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
6 | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx |
7 | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx |
8 | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx |
9 | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx |
10 | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
... | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx |
# | poi_id |
date |
period |
time_period |
popularity |
---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx |
2 | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx |
3 | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx |
4 | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
5 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx |
6 | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
7 | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx |
8 | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
9 | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx |
10 | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx |
... | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx |
# | poi_id |
date |
popularity |
---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx |
2 | xxxxxxxxxx | Xxxxx | Xxxxxx |
3 | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx |
4 | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx |
5 | xxxxxxxxx | Xxxxxxx | xxxxxx |
6 | Xxxxx | xxxxxxxxxx | xxxxxx |
7 | Xxxxxxxxxx | xxxxxx | Xxxxx |
8 | Xxxxxx | xxxxx | xxxxxxxx |
9 | xxxxxxx | Xxxxx | Xxxxxxxx |
10 | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
... | xxxxxx | Xxxxxxxxx | Xxxxxxxxx |
# | poi_id |
date |
reviews |
sentiment |
---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx |
2 | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx |
3 | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx |
4 | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx |
5 | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
6 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx |
7 | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx |
8 | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx |
9 | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx |
10 | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
... | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | ba5872298f911dc40fea1c7a651d2541ec67b3c2 | |
type
|
String | service_unavailable | |
value
|
String | wheelchair_accessible_entrance | |
date_last_checked
|
DateTime | 2024-02-28T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | ceff13ae5af1c7909f297cfc268cf8d1cc3576b3 | |
name
|
String | Cannibale Royale Rozengracht | |
street_address
|
String | Rozengracht 114 Amsterdam | |
latitude
|
Float | 52.373231 | |
longitude
|
Float | 4.87917 | |
industry
|
String | Food & Beverage | |
category
|
String | Restaurant | |
date_refreshed
|
DateTime | 2024-03-04T00:00:00+00:00 | |
name_translated
|
|||
country
|
String | netherlands | |
state
|
String | noord-holland | |
county
|
String | amsterdam | |
city
|
String | amsterdam | |
stars
|
|||
rooms
|
|||
price_class
|
Integer | 2 | |
sentiment
|
Float | 88.7 | |
popularity
|
Float | 87.05 | |
hours_popular
|
String | {"monday":"evening","tuesday":"evening","wednesday":"even... | |
main_clusters
|
String | [{"cluster": "Appearance","sentiment": 88.89},{"cluster":... | |
most_discussed_topics
|
String | [{"topic": "food","sentiment": 93.98},{"topic": "service"... | |
spoken_languages
|
String | [{"language": "en","sentiment": 86.52,"percentage": 59.62... | |
traveler_origin
|
|||
traveler_type
|
|||
phone
|
String | ||
website
|
String | http://www.cannibaleroyale.nl/ | |
brand_name
|
|||
date_first_presence
|
DateTime | 2019-03-13T00:00:00+00:00 | |
date_closed
|
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | b13bcd15bf8bcb7ded53663446603b3ae76111b5 | |
day_of_week
|
Integer | 1 | |
period_time
|
Integer | 1 | |
open_time
|
String | 10:00 | |
close_time
|
String | 19:00 | |
date_last_checked
|
DateTime | 2024-02-28T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 9a53b82957fb8b2fa1fb590dc72940acdd083fbd | |
date
|
DateTime | 2021-12-01T00:00:00+00:00 | |
period
|
String | weekend | |
time_period
|
String | (05-10) Early Morning | |
popularity
|
Float | 9.04 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 5c9bb8d616f30db5a5d66193cc845e85508abd93 | |
date
|
DateTime | 2022-02-01T00:00:00+00:00 | |
popularity
|
Float | 46.18 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | c19020c87d3f76fb8ccc4ba5cfe84d6caf5d9b21 | |
date
|
DateTime | 2022-03-01T00:00:00+00:00 | |
reviews
|
Integer | 2 | |
sentiment
|
Float | 66.25 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | 9fbf6902-3259-43e0-b84d-c802b1940899 | POI ID | |
String | POI Name | ||
String | Address | ||
Decimal | 40.786342970476895 | Latitude | |
Decimal | -119.2065156609571 | Longitude | |
String | Advertising | Company Industry | |
String | POI Category | ||
date_refreshed
|
Date | ||
String | United States of America | Country Name | |
String | California | State Name | |
String | Bernalillo County | County Name | |
String | Berlin | City Name | |
stars
|
Integer | ||
rooms
|
Integer | ||
price_class
|
Integer | ||
sentiment
|
Decimal | ||
popularity
|
Decimal | ||
hours_popular
|
String | {"monday":null,"tuesday":"afternoon","wednesday":"late_mo... | |
main_clusters
|
Decimal | [{"cluster": "Atmosphere","sentiment": 76.99},{"cluster":... | |
most_discussed_topics
|
Decimal | [{"topic": "service","sentiment": 78.57},{"topic": "staff... | |
spoken_languages
|
Decimal | [{"language": "it","sentiment": 85.93,"percentage": 94.39... | |
traveler_origin
|
Decimal | [{"country": "it","sentiment": 84.67,"percentage": 19.93}... | |
traveler_type
|
Decimal | [{"traveler_type": "couple","sentiment": 83.51,"ercentage... | |
String | Company Phone Number | ||
String | https://www.ibm.com | Company Website | |
date_first_presence
|
Date | ||
date_closed
|
Date |
Description
Country Coverage
History
Volume
137 | Online Sources Monitored |
195 | Countries Mapped |
251 | Million Points of Interest Mapped |
320 | Billion Pieces of Online Content Analyzed Each Day |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
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Frequently asked questions
What is The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data?
Explore up-to-date Geospatial Data across 180+ countries and 800+ brands and business categories. Connect with our experts to enhance your strategy with precise, accurate Location Data data to elevate your approach to the next level.
What is The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data used for?
This product has 5 key use cases. The Data Appeal Company recommends using the data for Location Intelligence, Out-of-home (OOH) Advertising, Retail Site Selection, Sentiment Analysis, and Marketing Data Enrichment. Global businesses and organizations buy Location Data from The Data Appeal Company to fuel their analytics and enrichment.
Who can use The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Location Data. Get in touch with The Data Appeal Company to see what their data can do for your business and find out which integrations they provide.
How far back does the data in The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data go?
This product has 4 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data cover?
This product includes data covering 249 countries like USA, China, Japan, Germany, and India. The Data Appeal Company is headquartered in Italy.
How much does The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data cost?
Pricing information for The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data is available by getting in contact with The Data Appeal Company. Connect with The Data Appeal Company to get a quote and arrange custom pricing models based on your data requirements.
How can I get The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data?
Businesses can buy Location Data from The Data Appeal Company and get the data via S3 Bucket, SFTP, Email, and REST API. Depending on your data requirements and subscription budget, The Data Appeal Company can deliver this product in .csv and .xls format.
What is the data quality of The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data?
The Data Appeal Company has reported that this product has the following quality and accuracy assurances: 95% match rate. You can compare and assess the data quality of The Data Appeal Company using Datarade’s data marketplace. The Data Appeal Company has received 3 reviews from clients. The Data Appeal Company appears on selected Datarade top lists ranking the best data providers, including Who’s New on Datarade? .
What are similar products to The Data Appeal Geospatial Data 251 Million POIs Mapped GDPR-compliant 5 Years of Historic Data?
This product has 3 related products. These alternatives include The Data Appeal Consumer Data API & Dataset 251 POI Mapped 180+ countries GDPR-Compliant Historical Data Since 2019, Grepsr Comprehensive Dataset of Walgreens US Stores Across the United States, and Global Leading Multinational Retailer Data. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.