Salutary Data | AI & ML Training Data | 100MM+ U.S Identities for Model Training | Identity Resolution | Identity Verification
# | Work Email Disposition |
evUpdatedDate |
emailDomain |
job_start_date |
recent_job_change |
twitter_url |
education |
experience |
|||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | Xxxxx | 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 |
3 | 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 | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx |
4 | 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 |
5 | 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 |
6 | 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 | Xxxxxxx | Xxxxxxxx | Xxxxxxx |
7 | 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 | xxxxxxx | Xxxxxx | Xxxxx |
8 | 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 |
9 | 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 | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx |
10 | 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 | 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 |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | 406E2447587ED0545136EED636C743B0 | UID | |
String | Contact First Name | ||
String | Contact Middle Name | ||
String | Contact Last Name | ||
String | Contact Gender | ||
String | Contact Age | ||
String | Contact Phone Number | ||
String | Organization Phone Number | ||
String | Contact Mobile Phone Number | ||
String | Contact Work Email Address | ||
Work Email Disposition
|
String | V | |
evUpdatedDate
|
Timestamp | 12/1/2022 | |
emailDomain
|
String | wellsfargo.com | |
String | Contact Email Address | ||
String | Contact Email Address | ||
String | Address | ||
String | Spokane | City Name | |
String | WA | State Abbreviation | |
Integer | 99201 | Postal Code | |
String | 420 Montgomery Street | Company Address | |
String | San Francisco | City Name | |
String | CA | State Abbreviation | |
Integer | 94104 | Postal Code | |
String | Address | ||
String | Liberty Lake | City Name | |
String | WA | State Abbreviation | |
Integer | 99019 | Postal Code | |
String | General Manager | Contact Job Title | |
String | Manager | Job Level | |
String | Business Management | Job Function | |
String | Wells Fargo | Company Name | |
String | Wellsfargo.com | Company Domain | |
job_start_date
|
Timestamp | 1/1/2004 | |
recent_job_change
|
String | FALSE | |
String | Contact LinkedIn | ||
String | Contact Facebook URL | ||
twitter_url
|
String | twitter.com/b###### | |
education
|
String | [{school: Kent State University, end_date: 2015, start_da... | |
experience
|
String | [{title: Project Manager, end_date: 2010-08, start_date: ... |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Contact First Name | ||
String | Contact Middle Name | ||
String | Contact Last Name | ||
String | Contact Gender | ||
String | Contact Age | ||
String | UID | ||
String | Contact Phone Number | ||
String | Company Phone Number | ||
String | Contact Mobile Phone Number | ||
String | Contact Work Email Address | ||
Work Email Disposition
|
String | ||
String | Contact Email Address | ||
String | Contact Email Address | ||
String | Address | ||
String | Berlin | City Name | |
String | NY | State Abbreviation | |
Integer | 10119 | Postal Code | |
String | Company Address | ||
String | Berlin | City Name | |
String | NY | State Abbreviation | |
Integer | 10119 | Postal Code | |
String | Address | ||
String | Berlin | City Name | |
String | NY | State Abbreviation | |
Integer | 10119 | Postal Code | |
String | Managing Director | Contact Job Title | |
String | Senior | Job Level | |
String | Procurement | Job Function | |
String | Coca Cola | Company Name | |
String | ibm.com | Company Domain | |
job_start_date
|
Timestamp | ||
recent_job_change
|
String | ||
String | Contact LinkedIn | ||
twitter_url
|
String | ||
education
|
String | ||
experience
|
String |
Description
Country Coverage
History
Volume
100 million | Identity Profiles |
Pricing
License | Starts at |
---|---|
One-off purchase | Not 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 Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification?
100MM+ US Identity profiles - Ideal for B2C / B2B applications requiring large amount of identity information. Well suited for Identity Resolution ML model training or Identity Graph Augmentation. Other use-cases include Identity Verification and Fraud Prevention.
What is Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification used for?
This product has 5 key use cases. Salutary Data recommends using the data for Machine Learning (ML), Data Science, Identity Resolution, People-Based Marketing, and Identity-Based Targeting. Global businesses and organizations buy Identity Graph Data from Salutary Data to fuel their analytics and enrichment.
Who can use Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Identity Graph Data. Get in touch with Salutary Data to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification go?
This product has 2 years of historical coverage. It can be delivered on a monthly, quarterly, and yearly basis.
Which countries does Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification cover?
This product includes data covering 1 country like USA. Salutary Data is headquartered in United States of America.
How much does Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification cost?
Pricing information for Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification is available by getting in contact with Salutary Data. Connect with Salutary Data to get a quote and arrange custom pricing models based on your data requirements.
How can I get Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification?
Businesses can buy Identity Graph Data from Salutary Data and get the data via S3 Bucket, SFTP, Email, and UI Export. Depending on your data requirements and subscription budget, Salutary Data can deliver this product in .json, .csv, and .xls format.
What is the data quality of Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification?
You can compare and assess the data quality of Salutary Data using Datarade’s data marketplace.
What are similar products to Salutary Data AI & ML Training Data 100MM+ U.S Identities for Model Training Identity Resolution Identity Verification?
This product has 3 related products. These alternatives include Redmob: Identity Graph USA HEMs & MAIDs I Identity Data I Device Graph I 700M Users, Factori Identity Data One Billion+ Identity Linkages, Validation and resolution Data , and Alesco Phone ID Database - Identity Graph Data with over 650 Million Phone Number, covers 94% of the US population - available for licensing!. You can compare the best Identity Graph Data providers and products via Datarade’s data marketplace and get the right data for your use case.