Employee Data

Clean Employee API

Data Dictionary: Clean Employee API

39min

Data dictionary for data retrieved using Clean Employee API endpoints. 
This data dictionary shows all available data points, explains their values, and provides data samples from the Clean Employee API data.  
﻿Base Employee Data﻿ 
﻿Employee API﻿ 
Categories
﻿Metadata﻿ 
﻿Identifiers﻿ 
﻿Skills﻿ 
﻿Experience﻿ 
﻿Education﻿ 
﻿Hidden collections﻿ 
﻿Location﻿ 
﻿Recommendations and connections﻿ 
﻿Languages﻿ 
﻿Certifications﻿ 
﻿Courses﻿ 
﻿Awards﻿ 
﻿Activity﻿ 
The data provided in the samples is strictly intended for illustrative purposes, allowing you to visualize its appearance and format. 
Metadata
Data point
Processing
Description
Data type 
last_updated
Cleaned
Date the record was last updated
String
is_deleted
Raw
Indicates whether the profile was accessible:
1 – deleted or private
0 – publicly available
Integer
Meta data
"last_updated": "2023-07-29",
"is_deleted": 0
"last_updated": "2023-07-29",
"is_deleted": 0
﻿
Data point
Cleaning action
last_updated
Value is converted to the yyyy-mm-dd format.
﻿
Identifiers
Data point
Processing
Description
Data type
id
Raw
Employee record identification key in our database
Integer
full_name 
Cleaned
Full name
String
name_first
Raw
First name 
String
name_middle
Enriched
Middle name 
String
name_last
Enriched
Last name
String
websites_professional_network
Raw
Professional network profile URL
String
shorthand_names
Raw
Historical shorthand name list
Array of strings
picture_url
Raw
Profile picture URL
String
follower_count
Raw
Profile follower count
Integer
Identifiers
{
  "id": 4290,
  "full_name": "John Leonardo Doe",
  "name_first": "John",
  "name_middle": "Leonardo",
  "name_last": "Doe",
  "websites_professional_network": "https://www.professional_network.com/in/john-leonardo-doe",
  "shorthand_names": [
    "john-leonardo-doe"
  ],
  "picture_url": "https://static.lnk.com/sc/h/9c8pery4andzj6ohjkjp54ma2",
  "follower_count": 445,
{
  "id": 4290,
  "full_name": "John Leonardo Doe",
  "name_first": "John",
  "name_middle": "Leonardo",
  "name_last": "Doe",
  "websites_professional_network": "https://www.professional_network.com/in/john-leonardo-doe",
  "shorthand_names": [
    "john-leonardo-doe"
  ],
  "picture_url": "https://static.lnk.com/sc/h/9c8pery4andzj6ohjkjp54ma2",
  "follower_count": 445,
﻿
Data point
Cleaning action
full_name
Special characters/emojis are removed; 
Any words that follow a comma or in parentheses are removed;
Titles (preceding or following the name) are removed.
name_middle
Parsed from member_full_name.
name_last
Parsed from member_full_name.
﻿
Skills
Data point
Processing
Description
Data type
skills
Enriched
Skill list
Array of strings
Skills
"skills": [
        "3d",
        "3d printing",
        "creative",
        "design",
        "electronics",
        "photography",
        "programming"
    ]
"skills": [
        "3d",
        "3d printing",
        "creative",
        "design",
        "electronics",
        "photography",
        "programming"
    ]
﻿
Data point
Enriching action
skills
Enriched with our ML model from different description fields. 
﻿
Experience
Data point
Processing
Description
Data type 
description
Raw
Job position description
String
company_id
Enriched
Employer's identification key
Integer
headline
Raw
Title found in the profile headline 
String
generated_headline
Raw
A user-written headline that can be found in web search, also viewed and other publicly available spaces.
It serves the same purpose as the title but is derived from a different source, potentially providing more accurate and up-to-date profile information. 
This field should be used in place title as it reflects the latest user activity.
String
job_title
Cleaned
Current job position title
String
is_decision_maker
Enriched
Indicates whether the employee is a decision-maker based on job_title
1 – Employee is marked a decision-maker in the current role 
0 – Employee is not marked a decision-maker in the current role
Integer
job_description
Raw
Current job position description
String
total_experience_duration
Enriched
Summed up experience. 
Converted to Professional network-like text, e.g., 
2 Years 11 Months
String
total_experience_duration_months
Enriched
Summed up experience (displayed as months)
Integer
Experience
"company_id": 10101010,
"description": "Examples Engineer, with a Master's Degree in Examples.",
"headline": "Examples Engineer @ Example Company",
"generated_headline": "Examples Engineer @ Example Company",
"job_title": "Examples Engineer",
"job_description": "Advice on the Examples generation.\\\\nWe develop Examples Modeling and Custom Examples",
"total_experience_duration": "2 Years 11 Months"
"total_experience_duration_months": 35, 
"company_id": 10101010,
"description": "Examples Engineer, with a Master's Degree in Examples.",
"headline": "Examples Engineer @ Example Company",
"generated_headline": "Examples Engineer @ Example Company",
"job_title": "Examples Engineer",
"job_description": "Advice on the Examples generation.\\\\nWe develop Examples Modeling and Custom Examples",
"total_experience_duration": "2 Years 11 Months"
"total_experience_duration_months": 35, 
﻿
Data point
Cleaning/enriching action 
company_id
Company ID from an active experience record from member_experience.
job_title
Special characters are removed.
date_from
Value is converted to the yyyy-mm-dd format.
total_experience_duration
Values converted to readable text.
total_experience_duration_months
Field aggregated from duration values.
﻿
The experience table is mapped with our historical data due to source's policy of hiding the work experience on certain employees' profiles. 
Data point
Processing
Description
Data type 
experience
-
Work experience details
Array of objects
company_id
Raw
Workplace (company) identifier in our database
Integer
date_from
Cleaned
Employment start date 
String (date)
date_from_year
Cleaned
Employment start year 
Integer
date_from_month
Cleaned
Employment start month 
Integer
date_to
Cleaned
Employment end date
String (date)
date_to_year
Cleaned
Employment end year
Integer
date_to_month
Cleaned
Employment end month
Integer
company_url
Raw
Employer's professional network profile URL
String
company_name
Raw
Employer company
﻿
title
Raw
Job title
String
department
Enriched
Associated department
String
management_level
Enriched
Management level 
String
description
Cleaned
Job description
String
order_in_profile
Raw
Record order as seen on the employee's profile
Integer
duration
Enriched
Employment duration
String (date)
duration_months
Cleaned
Employment duration in months
Integer
location
Cleaned
Job/workplace location
String
Experience
"experience": [
    {
      "title": "Product Owner, Sr. Salesforce Administrator",
      "description": "Best practice declarative management of Salesforce for the organization. Responsible for security protocols, permissions and profiles and daily maintenance of Salesforce. Custom declarative development for the organization.",
      "order_in_profile": 9,
      "company_id": 9975614,
      "company_name": "Example Company",
      "company_url": "https://www.professional_network.com/company/example-company",
      "date_from": "2013-10-01",
      "date_from_year": 2013,
      "date_from_month": 10,
      "date_to": "2015-07-01",
      "date_to_year": 2015,
      "date_to_month": 7,
      "duration": "1 year 10 months",
      "duration_months": 22,
      "department": "Product",
      "management_level": "Senior"
    }
],
"experience": [
    {
      "title": "Product Owner, Sr. Salesforce Administrator",
      "description": "Best practice declarative management of Salesforce for the organization. Responsible for security protocols, permissions and profiles and daily maintenance of Salesforce. Custom declarative development for the organization.",
      "order_in_profile": 9,
      "company_id": 9975614,
      "company_name": "Example Company",
      "company_url": "https://www.professional_network.com/company/example-company",
      "date_from": "2013-10-01",
      "date_from_year": 2013,
      "date_from_month": 10,
      "date_to": "2015-07-01",
      "date_to_year": 2015,
      "date_to_month": 7,
      "duration": "1 year 10 months",
      "duration_months": 22,
      "department": "Product",
      "management_level": "Senior"
    }
],
﻿
Data point
Cleaning/enriching action 
company_id
Company ID from an active experience record from member_experience.
job_title
Special characters are removed.
total_experience_duration
Values converted to readable text.
total_experience_duration_months
Field aggregated from duration values.
﻿
Information in the table below is enriched using Clean and Base Company datasets.
Data point
Description
Data type 
experience
Employer (company) details
Array of objects
company_type
Type
String
company_founded
Founding year
String
company_followers_count
Follower count
Integer
company_website
Official website
String
company_facebook_url
Facebook profile URL
Array of strings
company_twitter_url
Twitter profile URL
Array of strings
company_professional_network_url
Professional network profile URL
String
company_size_range
Size (as a range)
String
company_size_employees_count
Headcount
Integer
company_industry
Associated industry
String
company_location_hq_full_address
Full address of company headquarters
String
company_location_hq_country
Headquarters location (country)
String
company_location_hq_regions
Headquarters location (regions)
Array of strings
company_location_hq_country_iso2
Headquarters location (country, ISO alpha-2 code)
String
company_location_hq_country_iso3
Headquarters location (country, ISO alpha-3 code)
String
company_location_hq_city
Headquarters location (city)
String
company_location_hq_state
Headquarters location (state)
String
company_location_hq_street
Headquarters location (street)
String
company_location_hq_zipcode
Headquarters location (zipcode)
String
company_last_updated
The last update date of the company profile
String
company_categories_and_keywords
Categories and keywords assigned to the profile
Array of strings
company_stock_ticker
Stock ticker
Array of strings
company_is_b2b
Marks if the company sells B2B or B2C products
1 – b2b company 
0 – b2c company
Integer
company_annual_revenue
Annual revenue
Integer
company_annual_revenue_currency
Annual revenue currency
String
company_employees_count_change_yearly_percentage
Percentage of employee count change
String
company_last_funding_round_announced_date
Date of last funding round
String (date)
company_last_funding_round_amount_raised
Amount of last funding round
Integer
Experience + company
  "experience": [
    {
      "company_type": "Privately Held",
      "company_founded": "1939",
      "company_followers_count": 256699,
      "company_website": "www.example-company.com",
      "company_facebook_url": [
        "https://www.facebook.com/example-company"
      ],
      "company_twitter_url": [
        "https://www.twitter.com/example-company"
      ],
      "company_professional_network_url": "https://www.professional_network.com/company/example-company",
      "company_size_range": "5001-10,000 employees",
      "company_size_employees_count": 4488,
      "company_industry": "Truck Transportation",
      "company_location_hq_full_address": "15047; Lima, Lima Perú, PE",
      "company_location_hq_country": "Peru",
      "company_location_hq_regions": [
        "Americas",
        "Latin America and the Caribbean",
        "South America",
        "AMER"
      ],
      "company_location_hq_country_iso2": "PE",
      "company_location_hq_country_iso3": "PER",
      "company_location_hq_city": "Lima",
      "company_location_hq_state": "Example State",
      "company_location_hq_street": "Example Street",
      "company_location_hq_zipcode": "0033",
      "company_last_updated": "2024-08-29",
      "company_categories_and_keywords": [
        "Logistics"
      ],
      "company_stock_ticker": [
        "EXMP"
      ],
      "company_is_b2b": 1,
      "company_annual_revenue": 2500000000,
      "company_annual_revenue_currency": "$",
      "company_employees_count_change_yearly_percentage": 9.463414634146341,
      "company_last_funding_round_announced_date": "2023-06-05",
      "company_last_funding_round_amount_raised": 15600000
    }
  ]
  "experience": [
    {
      "company_type": "Privately Held",
      "company_founded": "1939",
      "company_followers_count": 256699,
      "company_website": "www.example-company.com",
      "company_facebook_url": [
        "https://www.facebook.com/example-company"
      ],
      "company_twitter_url": [
        "https://www.twitter.com/example-company"
      ],
      "company_professional_network_url": "https://www.professional_network.com/company/example-company",
      "company_size_range": "5001-10,000 employees",
      "company_size_employees_count": 4488,
      "company_industry": "Truck Transportation",
      "company_location_hq_full_address": "15047; Lima, Lima Perú, PE",
      "company_location_hq_country": "Peru",
      "company_location_hq_regions": [
        "Americas",
        "Latin America and the Caribbean",
        "South America",
        "AMER"
      ],
      "company_location_hq_country_iso2": "PE",
      "company_location_hq_country_iso3": "PER",
      "company_location_hq_city": "Lima",
      "company_location_hq_state": "Example State",
      "company_location_hq_street": "Example Street",
      "company_location_hq_zipcode": "0033",
      "company_last_updated": "2024-08-29",
      "company_categories_and_keywords": [
        "Logistics"
      ],
      "company_stock_ticker": [
        "EXMP"
      ],
      "company_is_b2b": 1,
      "company_annual_revenue": 2500000000,
      "company_annual_revenue_currency": "$",
      "company_employees_count_change_yearly_percentage": 9.463414634146341,
      "company_last_funding_round_announced_date": "2023-06-05",
      "company_last_funding_round_amount_raised": 15600000
    }
  ]
﻿
﻿
Data point
Processing
Description
Data type 
department
Enriched
Departments derived from the job_title
String
management_level
Enriched
Management levels identified from the job_title
String
is_working
Enriched
Current employment marker

1 – Currently employed
0 – Currently unemployed
Boolean
Experience
"department": "Project",
"management_level": "Other",
"is_working": 1
"department": "Project",
"management_level": "Other",
"is_working": 1
﻿
Data point
Cleaning/enriching action 
department
Enriched with our ML model.
management_level
Enriched with our ML model.
is_working
Based on date_to and date_from values of employee experience. 
﻿
Education
Data point
Processing
Description
Data type 
education
﻿
Education details
Array of objects
major
Cleaned
Field of study
String
title
Cleaned
Educational institution
String
date_to
Cleaned
Graduation date
Integer
date_from
Cleaned
Enrolment date
Integer
institution_url
Cleaned
Institution's profile URL
String
description
Cleaned
Education description
String
activities_and_societies
Cleaned
Details about activities and societies
String
Education
 "education": [
        {
            "major": "Associate's degree, Business Administration and Management, General",
            "title": "Example College",
            "date_to": "1997",
            "date_from": "1996",
            "institution_url": "https://www.professional_network.com/school/example-college",
            "description": "Attended Business College from 1996 to 1997",
            "activities_and_societies": "Activities and Societies: Chess"
        }
    ],
 "education": [
        {
            "major": "Associate's degree, Business Administration and Management, General",
            "title": "Example College",
            "date_to": "1997",
            "date_from": "1996",
            "institution_url": "https://www.professional_network.com/school/example-college",
            "description": "Attended Business College from 1996 to 1997",
            "activities_and_societies": "Activities and Societies: Chess"
        }
    ],
﻿
Data point
Cleaning action
title
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Values are capitalized. 
major
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from
Value is converted to the yyyy format.
date_to
Value is converted to the yyyy format.
institution_url
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
description
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
Text styling tags are removed; 
Multiple spaces are replaced with single ones.
activities_and_societies
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
Text styling tags are removed; 
Multiple spaces are replaced with single ones.
﻿
Hidden collections
Data point
Description
Data type 
is_hidden
Marks if the profile has a hidden education/experience collection.

0 – education/experience information was available at the time of profile scraping
1 – education/experience information was not available at the time of profile scraping
Boolean
is_hidden + experience
is_hidden + education
"experience": [
    {
        "title": "IT Project Manager",
        "description": "Lead cross-functional teams to deliver complex software solutions on time and within budget, overseeing all phases of project lifecycle from conception to deployment.",
        "order_in_profile": 1,
        "company_id": 11110108,
        "company_name": "Example Company",
        "professional_network_company_url": "https://www.professional_network.com/company/example-company",
        "date_from": "2022-06-01",
        "date_to": null,
        "duration": "1 year"
    }
],
"is_hidden": 0,
"experience": [
    {
        "title": "IT Project Manager",
        "description": "Lead cross-functional teams to deliver complex software solutions on time and within budget, overseeing all phases of project lifecycle from conception to deployment.",
        "order_in_profile": 1,
        "company_id": 11110108,
        "company_name": "Example Company",
        "professional_network_company_url": "https://www.professional_network.com/company/example-company",
        "date_from": "2022-06-01",
        "date_to": null,
        "duration": "1 year"
    }
],
"is_hidden": 0,
﻿
﻿
Location
Data point
Processing
Description
Data type 
location_raw_address
Cleaned
Associated location
String
location_country
Cleaned
Parsed country
String
location_regions
Cleaned
Geographical regions parsed from associated location
Array of strings
Location
"location_raw_address": "Peru",
"location_country": "Peru",
"location_regions": [
        "AMER",
        "South America",
        "Latin America and the Caribbean"
    ],
"location_raw_address": "Peru",
"location_country": "Peru",
"location_regions": [
        "AMER",
        "South America",
        "Latin America and the Caribbean"
    ],
﻿
Data point
Cleaning action
location_raw_address
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Special trailed characters are trimmed; 
Value is set to None if it is shorter than three characters; 
The value of member_location_country is added at the end of the string.
location_country
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None. 
﻿
Recommendations and connections
Data point
Processing
Description
Data type 
recommendations
Cleaned
Recommendations from other users
Array of objects
recommendation
Cleaned
Recommendation text
String
referee_name
Raw
Referee's name
String
referee_url
Raw
Referee's profile URL
String
recommendations_count
Cleaned
Number of received recommendations
Integer
connections_count
Raw
Number of connections with other users
Integer
Recommendations and connections
"recommendations": [
    {
      "recommendation": "“John was a great asset in collaborating the tasks in different departments to produce the same goal. He was great at providing advice and asking questions to avoid even a tiny error during the process. Great to work with him!”",
      "referee_name": "Marry Moe",
      "referee_url": "www.professional_network.com/in/marry-moe",
      "order_in_profile": 1
    }
  ],
  "recommendations_count": 1,
  "connections_count": 65535,
"recommendations": [
    {
      "recommendation": "“John was a great asset in collaborating the tasks in different departments to produce the same goal. He was great at providing advice and asking questions to avoid even a tiny error during the process. Great to work with him!”",
      "referee_name": "Marry Moe",
      "referee_url": "www.professional_network.com/in/marry-moe",
      "order_in_profile": 1
    }
  ],
  "recommendations_count": 1,
  "connections_count": 65535,
﻿
Data point
Cleaning action
recommendations
Deleted rows are filtered out. 
recommendation
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Value is set to None if it is shorter than three characters; 
Text styling tags are removed; 
Multiple spaces are replaced with single ones; 
Empty recommendations are filtered out. 
recommendations_count
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
None values are replaced with 0 and made an integer. 
﻿
Languages
Data point
Processing
Description
Data type 
languages
﻿
Language knowledge
Array of objects
language
Cleaned
Language
String
proficiency
Cleaned
Language proficiency
String
order_in_profile
Raw
Record order in the section
Integer
Languages
"languages": [
        {
            "language": "English",
            "proficiency": "Intermediate",
            "order_in_profile": 1
        }
    ],
"languages": [
        {
            "language": "English",
            "proficiency": "Intermediate",
            "order_in_profile": 1
        }
    ],
﻿
Data point
Cleaning action
language
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
proficiency
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
﻿
Certifications
Data point
Processing
Description
Data type 
certifications
﻿
Held certifications
Array of objects
title
Cleaned
Certificate title
String
issuer
Cleaned
Certificate issuer
String
credential_id
Cleaned
Record order in the section
Integer
certificate_url
Cleaned
Certificate URL
String
date_from
Cleaned
Issue date 
String
date_to
Cleaned
Expiration date
String
issuer_url
Cleaned
Issuer profile URL
String
order_in_profile
Raw
Section record order
Integer
date_from_year
Cleaned
Issue year
Integer
date_from_month
Cleaned
Issue month
Integer
date_to_year
Cleaned
Expiration year
Integer
date_to_month
Cleaned
Expiration month
Integer
Certifications
"certifications": [
        {
            "title": "Yellow Certificate",
            "issuer": "Example Studio",
            "credential_id": 3344,
            "certificate_url": "http://example-studio.com/public_profile_certification-title",
            "date_from": "2020-08-01",
            "date_from_year": 2020,
            "date_from_month": 8,
            "date_to": "2023-08-01",
            "date_to_year": 2023,
            "date_to_year": 8,
            "issuer_url": "https://www.professional_network.com/company/example-studio",
            "order_in_profile": 1
        }
    ],
"certifications": [
        {
            "title": "Yellow Certificate",
            "issuer": "Example Studio",
            "credential_id": 3344,
            "certificate_url": "http://example-studio.com/public_profile_certification-title",
            "date_from": "2020-08-01",
            "date_from_year": 2020,
            "date_from_month": 8,
            "date_to": "2023-08-01",
            "date_to_year": 2023,
            "date_to_year": 8,
            "issuer_url": "https://www.professional_network.com/company/example-studio",
            "order_in_profile": 1
        }
    ],
﻿
Data point
Cleaning action
title
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
issuer
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from
Value is converted to the yyyy-mm-dd format.
date_to
Value is converted to the yyyy-mm-dd format.
issuer_url
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from_year
date_to_year
Year value from date is converted to an integer.
date_from_month
date_to_month
Month value from date is converted to an integer.
﻿
Courses
Data point
Processing
Description
Data type 
courses
﻿
Attended courses
Array of objects
organizer
Cleaned
Course organizer
String
title
Cleaned
Course title
String
order_in_profile
Raw
Record order in the section
Integer
Courses
 "courses": [
        {
            "organizer": "Example Academy",
            "title": "Microsoft Certified Excel Expert",
            "order_in_profile": 1
        }
    ],
 "courses": [
        {
            "organizer": "Example Academy",
            "title": "Microsoft Certified Excel Expert",
            "order_in_profile": 1
        }
    ],
﻿
Data point
Cleaning action
organizer
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
title
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
﻿
Awards
Data point
Processing
Description
Data type 
awards
﻿
Held awards
Array of objects
title
Cleaned
Award
String
issuer
Cleaned
Award issuer
String
description
Cleaned
Award description
String
date
Cleaned
Issue date 
String
order_in_profile
Raw
Section record order
Integer
date_year
Cleaned
Issue year
Integer
date_month
Cleaned
Issue month
Integer
Awards
"awards": [
        {
            "title": "Certified in Example Management",
            "issuer": "Example Association",
            "description": "Certification in Example Management",
            "date": "2011-08-01",
            "order_in_profile": 4,
            "date_year": 2011,
            "date_month": 8
        }
    ],
"awards": [
        {
            "title": "Certified in Example Management",
            "issuer": "Example Association",
            "description": "Certification in Example Management",
            "date": "2011-08-01",
            "order_in_profile": 4,
            "date_year": 2011,
            "date_month": 8
        }
    ],
﻿
Data point
Cleaning action
title
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Values are capitalized. 
issuer
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date
Value is converted to the yyyy-mm-dd format.
date_year
Year value from date is converted to an integer.
date_month
Month value from date is converted to an integer.
﻿
Activity
Data point
Processing
Description
Data type 
activity
﻿
Interaction with posts on Professional network
Array of objects
activity_url
Raw
Post URL
String
title
Cleaned
Post title
String
action
Cleaned
Interaction type
String
order_in_profile
Raw
Section record order
Integer
Activity
"activity": [
        {
            "activity_url": "https://www.professional_network.com/posts/example-company-post1",
            "title": "Example Company would like to introduce our \"Team Spotlight”, John Doe @Example Company #example #company",
            "action": "Liked by",
            "order_in_profile": 1
        }
    ],
"activity": [
        {
            "activity_url": "https://www.professional_network.com/posts/example-company-post1",
            "title": "Example Company would like to introduce our \"Team Spotlight”, John Doe @Example Company #example #company",
            "action": "Liked by",
            "order_in_profile": 1
        }
    ],
﻿
Data point
Cleaning action 
title
﻿
Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Text styling tags removed;
Multiple spaces are replaced with single ones.
﻿

Data point	Processing	Description	Data type
last_updated	Cleaned	Date the record was last updated	String
is_deleted	Raw	Indicates whether the profile was accessible: 1 – deleted or private 0 – publicly available	Integer

Data point	Cleaning action
last_updated	Value is converted to the yyyy-mm-dd format.

Data point	Processing	Description	Data type
id	Raw	Employee record identification key in our database	Integer
full_name	Cleaned	Full name	String
name_first	Raw	First name	String
name_middle	Enriched	Middle name	String
name_last	Enriched	Last name	String
websites_professional_network	Raw	Professional network profile URL	String
shorthand_names	Raw	Historical shorthand name list	Array of strings
picture_url	Raw	Profile picture URL	String
follower_count	Raw	Profile follower count	Integer

Data point	Cleaning action
full_name	Special characters/emojis are removed; Any words that follow a comma or in parentheses are removed; Titles (preceding or following the name) are removed.
name_middle	Parsed from member_full_name.
name_last	Parsed from member_full_name.

Data point	Processing	Description	Data type
skills	Enriched	Skill list	Array of strings

Data point	Enriching action
skills	Enriched with our ML model from different description fields.

Data point	Processing	Description	Data type
description	Raw	Job position description	String
company_id	Enriched	Employer's identification key	Integer
headline	Raw	Title found in the profile headline	String
generated_headline	Raw	A user-written headline that can be found in web search, also viewed and other publicly available spaces. It serves the same purpose as the title but is derived from a different source, potentially providing more accurate and up-to-date profile information. This field should be used in place title as it reflects the latest user activity.	String
job_title	Cleaned	Current job position title	String
is_decision_maker	Enriched	Indicates whether the employee is a decision-maker based on job_title 1 – Employee is marked a decision-maker in the current role 0 – Employee is not marked a decision-maker in the current role	Integer
job_description	Raw	Current job position description	String
total_experience_duration	Enriched	Summed up experience. Converted to Professional network-like text, e.g., 2 Years 11 Months	String
total_experience_duration_months	Enriched	Summed up experience (displayed as months)	Integer

Data point	Cleaning/enriching action
company_id	Company ID from an active experience record from member_experience.
job_title	Special characters are removed.
date_from	Value is converted to the yyyy-mm-dd format.
total_experience_duration	Values converted to readable text.
total_experience_duration_months	Field aggregated from duration values.

Data point	Processing	Description	Data type
experience	-	Work experience details	Array of objects
company_id	Raw	Workplace (company) identifier in our database	Integer
date_from	Cleaned	Employment start date	String (date)
date_from_year	Cleaned	Employment start year	Integer
date_from_month	Cleaned	Employment start month	Integer
date_to	Cleaned	Employment end date	String (date)
date_to_year	Cleaned	Employment end year	Integer
date_to_month	Cleaned	Employment end month	Integer
company_url	Raw	Employer's professional network profile URL	String
company_name	Raw	Employer company
title	Raw	Job title	String
department	Enriched	Associated department	String
management_level	Enriched	Management level	String
description	Cleaned	Job description	String
order_in_profile	Raw	Record order as seen on the employee's profile	Integer
duration	Enriched	Employment duration	String (date)
duration_months	Cleaned	Employment duration in months	Integer
location	Cleaned	Job/workplace location	String

Data point	Cleaning/enriching action
company_id	Company ID from an active experience record from member_experience.
job_title	Special characters are removed.
total_experience_duration	Values converted to readable text.
total_experience_duration_months	Field aggregated from duration values.

Data point	Description	Data type
experience	Employer (company) details	Array of objects
company_type	Type	String
company_founded	Founding year	String
company_followers_count	Follower count	Integer
company_website	Official website	String
company_facebook_url	Facebook profile URL	Array of strings
company_twitter_url	Twitter profile URL	Array of strings
company_professional_network_url	Professional network profile URL	String
company_size_range	Size (as a range)	String
company_size_employees_count	Headcount	Integer
company_industry	Associated industry	String
company_location_hq_full_address	Full address of company headquarters	String
company_location_hq_country	Headquarters location (country)	String
company_location_hq_regions	Headquarters location (regions)	Array of strings
company_location_hq_country_iso2	Headquarters location (country, ISO alpha-2 code)	String
company_location_hq_country_iso3	Headquarters location (country, ISO alpha-3 code)	String
company_location_hq_city	Headquarters location (city)	String
company_location_hq_state	Headquarters location (state)	String
company_location_hq_street	Headquarters location (street)	String
company_location_hq_zipcode	Headquarters location (zipcode)	String
company_last_updated	The last update date of the company profile	String
company_categories_and_keywords	Categories and keywords assigned to the profile	Array of strings
company_stock_ticker	Stock ticker	Array of strings
company_is_b2b	Marks if the company sells B2B or B2C products 1 – b2b company 0 – b2c company	Integer
company_annual_revenue	Annual revenue	Integer
company_annual_revenue_currency	Annual revenue currency	String
company_employees_count_change_yearly_percentage	Percentage of employee count change	String
company_last_funding_round_announced_date	Date of last funding round	String (date)
company_last_funding_round_amount_raised	Amount of last funding round	Integer

Data point	Processing	Description	Data type
department	Enriched	Departments derived from the job_title	String
management_level	Enriched	Management levels identified from the job_title	String
is_working	Enriched	Current employment marker 1 – Currently employed 0 – Currently unemployed	Boolean

Data point	Cleaning/enriching action
department	Enriched with our ML model.
management_level	Enriched with our ML model.
is_working	Based on date_to and date_from values of employee experience.

Data point	Processing	Description	Data type
education		Education details	Array of objects
major	Cleaned	Field of study	String
title	Cleaned	Educational institution	String
date_to	Cleaned	Graduation date	Integer
date_from	Cleaned	Enrolment date	Integer
institution_url	Cleaned	Institution's profile URL	String
description	Cleaned	Education description	String
activities_and_societies	Cleaned	Details about activities and societies	String

Data point	Cleaning action
title	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; Values are capitalized.
major	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from	Value is converted to the yyyy format.
date_to	Value is converted to the yyyy format.
institution_url	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
description	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None. Text styling tags are removed; Multiple spaces are replaced with single ones.
activities_and_societies	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None. Text styling tags are removed; Multiple spaces are replaced with single ones.

Data point	Description	Data type
is_hidden	Marks if the profile has a hidden education/experience collection. 0 – education/experience information was available at the time of profile scraping 1 – education/experience information was not available at the time of profile scraping	Boolean

Data point	Processing	Description	Data type
location_raw_address	Cleaned	Associated location	String
location_country	Cleaned	Parsed country	String
location_regions	Cleaned	Geographical regions parsed from associated location	Array of strings

Data point	Cleaning action
location_raw_address	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; Special trailed characters are trimmed; Value is set to None if it is shorter than three characters; The value of member_location_country is added at the end of the string.
location_country	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Data point	Processing	Description	Data type
recommendations	Cleaned	Recommendations from other users	Array of objects
recommendation	Cleaned	Recommendation text	String
referee_name	Raw	Referee's name	String
referee_url	Raw	Referee's profile URL	String
recommendations_count	Cleaned	Number of received recommendations	Integer
connections_count	Raw	Number of connections with other users	Integer

Data point	Cleaning action
recommendations	Deleted rows are filtered out.
recommendation	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; Value is set to None if it is shorter than three characters; Text styling tags are removed; Multiple spaces are replaced with single ones; Empty recommendations are filtered out.
recommendations_count	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; None values are replaced with 0 and made an integer.

Data point	Processing	Description	Data type
languages		Language knowledge	Array of objects
language	Cleaned	Language	String
proficiency	Cleaned	Language proficiency	String
order_in_profile	Raw	Record order in the section	Integer

Data point	Cleaning action
language	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
proficiency	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Data point	Processing	Description	Data type
certifications		Held certifications	Array of objects
title	Cleaned	Certificate title	String
issuer	Cleaned	Certificate issuer	String
credential_id	Cleaned	Record order in the section	Integer
certificate_url	Cleaned	Certificate URL	String
date_from	Cleaned	Issue date	String
date_to	Cleaned	Expiration date	String
issuer_url	Cleaned	Issuer profile URL	String
order_in_profile	Raw	Section record order	Integer
date_from_year	Cleaned	Issue year	Integer
date_from_month	Cleaned	Issue month	Integer
date_to_year	Cleaned	Expiration year	Integer
date_to_month	Cleaned	Expiration month	Integer

Data point	Cleaning action
title	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
issuer	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from	Value is converted to the yyyy-mm-dd format.
date_to	Value is converted to the yyyy-mm-dd format.
issuer_url	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date_from_year date_to_year	Year value from date is converted to an integer.
date_from_month date_to_month	Month value from date is converted to an integer.

Data point	Processing	Description	Data type
courses		Attended courses	Array of objects
organizer	Cleaned	Course organizer	String
title	Cleaned	Course title	String
order_in_profile	Raw	Record order in the section	Integer

Data point	Cleaning action
organizer	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
title	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Data point	Processing	Description	Data type
awards		Held awards	Array of objects
title	Cleaned	Award	String
issuer	Cleaned	Award issuer	String
description	Cleaned	Award description	String
date	Cleaned	Issue date	String
order_in_profile	Raw	Section record order	Integer
date_year	Cleaned	Issue year	Integer
date_month	Cleaned	Issue month	Integer

Data point	Cleaning action
title	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; Values are capitalized.
issuer	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.
date	Value is converted to the yyyy-mm-dd format.
date_year	Year value from date is converted to an integer.
date_month	Month value from date is converted to an integer.

Data point	Processing	Description	Data type
activity		Interaction with posts on Professional network	Array of objects
activity_url	Raw	Post URL	String
title	Cleaned	Post title	String
action	Cleaned	Interaction type	String
order_in_profile	Raw	Section record order	Integer

Data point	Cleaning action
title	Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None; Text styling tags removed; Multiple spaces are replaced with single ones.

Clean Employee API

Sample: Clean Employee API

Data Dictionary: Clean Employee API

Other Employee data variations

﻿Base Employee Data﻿

﻿Employee API﻿

Metadata

Data sample

Cleaning actions

Identifiers

Data sample

Cleaning actions

Skills

Data sample

Enriching action

Experience

Data sample

Cleaning and enriching actions

Data sample

Cleaning and enriching actions

Data sample

Data sample

Enriching actions

Education

Data sample

Cleaning actions

Hidden collections

Data sample

Location

Data sample

Cleaning actions

Recommendations and connections

Data sample

Cleaning actions

Languages

Data sample

Cleaning actions

Certifications

Data sample

Cleaning actions

Courses

Data sample

Cleaning actions

Awards

Data sample

Cleaning actions

Activity

Data sample

Cleaning actions

Base Employee Data

Employee API