WebAutomation LinkedIn Profile Data | Global Linkedin Employee Profiles | 500M+ Records | GDPR Compliant | Monthly Updates
# | middle_initial |
middle_name |
full_name |
gender |
job_title |
summary |
job_summary |
industry |
birth_date |
birth_year |
certifications |
countries |
education |
experience |
location_locality |
location_metro |
location_name |
location_names |
location_postal_code |
location_region |
location_street_address |
location_address_line_2 |
location_continent |
location_country |
location_geo |
location_last_updated |
inferred_salary |
inferred_years_experience |
interests |
facebook_id |
facebook_url |
facebook_username |
github_url |
github_username |
id |
job_company_facebook_url |
job_company_founded |
job_company_id |
job_company_industry |
job_company_linkedin_id |
job_company_linkedin_url |
job_company_location_address_line_2 |
job_company_location_continent |
job_company_location_country |
job_company_location_geo |
job_company_location_locality |
job_company_location_metro |
job_company_location_name |
job_company_location_postal_code |
job_company_location_region |
job_company_location_street_address |
job_company_name |
job_company_size |
job_company_twitter_url |
job_company_website |
job_last_updated |
job_start_date |
job_title_levels |
job_title_role |
job_title_sub_role |
linkedin_connections |
linkedin_id |
linkedin_username |
profiles |
regions |
skills |
street_addresses |
twitter_url |
twitter_username |
version_status |
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4 | 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 | 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 |
5 | 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 | 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 |
6 | 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 | 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 |
7 | 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 | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx |
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9 | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxxx |
10 | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx |
... | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxx | Xxxxxx | Xxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Contact First Name | ||
middle_initial
|
String | None | |
middle_name
|
String | None | |
String | Contact Last Name | ||
full_name
|
String | ||
String | Company Email Address | ||
String | Email Address | ||
String | Contact Mobile Phone Number | ||
String | Phone Number | ||
gender
|
String | ||
job_title
|
String | deputy it program manager | |
summary
|
String | Versatile and solutions-focused IT PROGRAM MANAGER / PROC... | |
job_summary
|
String | Versatile and solutions-focused IT PROGRAM MANAGER / PROC... | |
industry
|
String | information technology and services | |
birth_date
|
String | None | |
birth_year
|
String | None | |
String | Contact LinkedIn | ||
certifications
|
String | [{'organization': 'comptia', 'start_date': '2016-03', 'en... | |
countries
|
String | ['united states'] | |
education
|
String | [{'school': {'name': 'western governors university', 'typ... | |
experience
|
String | [{'company': {'name': 'lockheed martin', 'size': '10001+'... | |
location_locality
|
String | owings | |
location_metro
|
String | district of columbia | |
location_name
|
String | owings, maryland, united states | |
location_names
|
String | ['moyock, north carolina, united states', 'suffolk, virgi... | |
location_postal_code
|
Integer | 20736 | |
location_region
|
String | maryland | |
location_street_address
|
String | 7020 decoy drive | |
location_address_line_2
|
String | None | |
location_continent
|
String | north america | |
location_country
|
String | united states | |
location_geo
|
String | 38.71,-76.60 | |
location_last_updated
|
String | 01/07/2020 | |
inferred_salary
|
String | 150,000-250,000 | |
inferred_years_experience
|
Integer | 1 | |
interests
|
String | [] | |
facebook_id
|
String | None | |
facebook_url
|
String | None | |
facebook_username
|
String | None | |
github_url
|
String | None | |
github_username
|
String | None | |
id
|
String | tn3tHWbJPcZHnnawpHDBKA_0000 | |
job_company_facebook_url
|
String | None | |
job_company_founded
|
Integer | 2001 | |
job_company_id
|
String | spalding-consulting-inc- | |
job_company_industry
|
String | information technology and services | |
job_company_linkedin_id
|
Integer | 1072568 | |
job_company_linkedin_url
|
String | linkedin.com/company/spalding-consulting-inc- | |
job_company_location_address_line_2
|
String | suite 200 | |
job_company_location_continent
|
String | north america | |
job_company_location_country
|
String | united states | |
job_company_location_geo
|
String | 38.26,-76.45 | |
job_company_location_locality
|
String | lexington park | |
job_company_location_metro
|
String | california, maryland | |
job_company_location_name
|
String | lexington park, maryland, united states | |
job_company_location_postal_code
|
Integer | 20653 | |
job_company_location_region
|
String | maryland | |
job_company_location_street_address
|
String | 46655 expedition drive | |
job_company_name
|
String | spalding consulting, inc. | |
job_company_size
|
String | 201-500 | |
job_company_twitter_url
|
String | twitter.com/spaldingjobs | |
job_company_website
|
String | scipax.com | |
job_last_updated
|
String | 01/11/2020 | |
job_start_date
|
String | 2016-02 | |
job_title_levels
|
String | ['manager'] | |
job_title_role
|
String | operations | |
job_title_sub_role
|
String | None | |
String | [] | Language Name | |
linkedin_connections
|
Integer | 127 | |
linkedin_id
|
Integer | 342743672 | |
linkedin_username
|
String | deborahcessna | |
profiles
|
String | [{'network': 'linkedin', 'id': '342743672', 'url': 'linke... | |
regions
|
String | ['maryland, united states', 'virginia, united states', 'n... | |
skills
|
String | ['databases', 'sql', 'requirements analysis', 'dod', 'int... | |
street_addresses
|
String | [{'name': 'lexington park, maryland, united states', 'loc... | |
twitter_url
|
String | None | |
twitter_username
|
String | None | |
version_status
|
String | {'status': 'updated', 'contains': [], 'previous_version':... |
Description
Country Coverage
Volume
50 million | Employee Records |
30 | Days Refresh |
Pricing
Suitable Company Sizes
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates?
Unlock the power of LinkedIn with our comprehensive dataset obtained through advanced web automation. Our Linkedin profiles dataset provides over 500 million employee profiles worldwide, enabling you to gain valuable insights into talent trends, industry dynamics, and professional connections.
What is WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates used for?
This product has 5 key use cases. Webautomation recommends using the data for Employment Analytics, B2B Lead Retargeting, HR Strategy, Lead Data Enrichment, and employee dataset. Global businesses and organizations buy Firmographic Data from Webautomation to fuel their analytics and enrichment.
Who can use WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Firmographic Data. Get in touch with Webautomation to see what their data can do for your business and find out which integrations they provide.
Which countries does WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates cover?
This product includes data covering 64 countries like USA, Germany, United Kingdom, France, and Italy. Webautomation is headquartered in United Kingdom.
How much does WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates cost?
Pricing information for WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates is available by getting in contact with Webautomation. Connect with Webautomation to get a quote and arrange custom pricing models based on your data requirements.
How can I get WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates?
Businesses can buy Firmographic Data from Webautomation and get the data via S3 Bucket, UI Export, and REST API. Depending on your data requirements and subscription budget, Webautomation can deliver this product in .json, .csv, .xls, and .txt format.
What is the data quality of WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates?
You can compare and assess the data quality of Webautomation using Datarade’s data marketplace. Webautomation has received 1 review from clients. Webautomation appears on selected Datarade top lists ranking the best data providers, including Best 5 Amazon Data Scrapers for Product Research & Analysis and Best Job Search APIs for Efficient Hiring.
What are similar products to WebAutomation LinkedIn Profile Data Global Linkedin Employee Profiles 500M+ Records GDPR Compliant Monthly Updates?
This product has 3 related products. These alternatives include Grepsr Company Data Firmographic Dataset from LinkedIn Global Coverage with Custom and On-demand Datasets, LinkedIn Continuum 90m US LinkedIn Profile Data B2B Professional Profiles Email Address Data , and LinkedIn Profile Database 2024 Buy LinkedIn Public Profile Dataset LinkedIn Contact Database 300M+Linekdin Profiles. You can compare the best Firmographic Data providers and products via Datarade’s data marketplace and get the right data for your use case.