Factori AI & ML Training Data | Mobility Data | Global | Machine Learning Data | Carrier, IP address, Hex8, Hex9 | Historical Location data
# | latitude |
longitude |
horizontal_accuracy |
timestamp |
id_type |
user_agent |
country |
state_hasc |
city_hasc |
postcode |
geohash |
hex8 |
hex9 |
carrier |
|||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx |
2 | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx |
3 | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx |
4 | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx |
5 | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx |
6 | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx |
7 | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx |
8 | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx |
9 | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx |
10 | 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 |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | MAID | ||
latitude
|
String | bfb04731cb0d2ad47c649f66d3d640e179cc69fc | |
longitude
|
String | a83a539a50c4ff70cd80827b42e73228fcff76b6 | |
horizontal_accuracy
|
Integer | 19 | |
timestamp
|
Integer | 1714571020 | |
id_type
|
Integer | 1 | |
String | IPv4 Address | ||
String | IPv6 Address | ||
user_agent
|
|||
country
|
String | USA | |
state_hasc
|
String | US.HI | |
city_hasc
|
String | US.HI.HA | |
postcode
|
Integer | 96737 | |
geohash
|
String | 8e3hx9ts | |
hex8
|
String | 885d13cec5fffff | |
hex9
|
String | 895d13cec4bffff | |
carrier
|
String | AT&T Wireless |
Attribute | Type | Example | Mapping |
---|---|---|---|
Anonymous ID
|
a264e175d4b1731a6969dee6f9e692e7 | ||
Float | 35.45 | Latitude | |
Float | 20.35 | Longitude | |
Carrier
|
Vodafone | ||
Timestamp
|
12/12/2019 08:34:55 | ||
ha_accuracy
|
7 | ||
String | IND | Country Name | |
String | IPv4 Address | ||
String | IPv6 Address | ||
id_type
|
1 | ||
user_agent
|
Mozilla/5.0 (Linux; Android 10; SH-02M Build/S5488; wv) A... | ||
String | JPN | Country Name | |
state_hasc
|
JP.AO | ||
city_hasc
|
JP.AO.AM | ||
String | 864 | Postal Code | |
geohash
|
wvug8s2k | ||
hex8
|
884b669933fffff | ||
hex9
|
884b669933fffff |
Description
Country Coverage
History
Volume
1.92 billion | Daily Location Pings |
305 | Average pings per month |
55 | Average pings per Day |
68 million | DAU (Daily Active users) |
206 million | MAU (Monthly Active Users) |
131 billion | Monthly Location Pings |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License | Not available |
Yearly License |
$360,000 / year |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data?
We provide high-quality persistent mobility data from our partnered mobile apps & SDKs and this data feed is aggregated from multiple data sources globally and is delivered as a daily feed. All data is collected and anonymized with clear consent and terms of usage.
What is Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data used for?
This product has 5 key use cases. Factori recommends using the data for Location Intelligence, Foot Traffic Analytics, Footfall Attribution, Mobile Advertising, and Foot Traffic Analysis. Global businesses and organizations buy Mobile Network Coverage from Factori to fuel their analytics and enrichment.
Who can use Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Mobile Network Coverage. Get in touch with Factori to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data go?
This product has 1 years of historical coverage. It can be delivered on a hourly, daily, weekly, monthly, and on-demand basis.
Which countries does Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data cover?
This product includes data covering 249 countries like USA, China, Japan, Germany, and India. Factori is headquartered in United States of America.
How much does Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data cost?
Pricing for Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data starts at USD360,000 per year. Connect with Factori to get a quote and arrange custom pricing models based on your data requirements.
How can I get Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data?
Businesses can buy Mobile Network Coverage from Factori and get the data via S3 Bucket and SFTP. Depending on your data requirements and subscription budget, Factori can deliver this product in .csv format.
What is the data quality of Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data?
Factori has reported that this product has the following quality and accuracy assurances: 99% Horizontal Accuracy. You can compare and assess the data quality of Factori using Datarade’s data marketplace. Factori has received 2 reviews from clients. Factori appears on selected Datarade top lists ranking the best data providers, including 10 Best Data Providers for 360 Customer View, 10 Best Data Providers for Customer Segmentation, and Best Data Providers For Location-Based Marketing.
What are similar products to Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data?
This product has 3 related products. These alternatives include Factori Mobility Data Global Mobile Location, Carrier, IP address, Hex8, Hex9 Historical Location data, Veraset Mobile Location Data GLOBAL GPS Mobility Data Reliable, Compliant, Precise Location Data 200+ Countries / 1.8B+ Devices Monthly, and Unacast Mobility Data - Global Mobile Location Data - Current & Historical. You can compare the best Mobile Network Coverage providers and products via Datarade’s data marketplace and get the right data for your use case.