What is Employee Data? Examples, Providers & Datasets to Buy
What is Employee Data?
Employee data is information collected and stored by an organization about its employees. It typically includes personal details such as name, address, contact information, social security number, date of birth, job title, salary, performance evaluations, attendance records, and benefits. It’s used for HR management, payroll processing, compliance with legal requirements, and workforce planning and development.
What Are Examples of Employee Data?
Examples of employee data include datasets offering insights into workforce composition and trends. Key examples include:
- Employee Demographics: Information such as age, gender, and location.
- Job Titles and Roles: Data on employee positions and responsibilities.
- Salary Information: Compensation details across roles and industries.
- Work History: Career paths, previous roles, and tenure at organizations.
- Skillsets and Certifications: Data on qualifications, certifications, and areas of expertise.
Editor's Pick
Best Employee Databases, Datasets & API
The best employee datasets provide comprehensive insights into workforce demographics, salaries, and professional trends. This curated list features the top employee datasets and APIs, selected for quality, accuracy, and trusted providers where you can buy employee data.
Employee Data | Employee Data API | Global | Fresh Data
B2B Continuum from Solution Publishing | 120M US B2B Professional Employee Data | US Employee Datasets | LinkedIn Reported Data
BIGDBM US B2B Company and Employee Contact Data
Employee Data API | Optimize HR Strategies & Find The Right Employees | Access 700M+ Professional Records | Best Price Guarantee
Bright Data | Linkedin Data - company/employee profiles (global coverage)
Factori US Firmographic data | Company data | B2B data | Stock Ticker, NAICS Code, Revenue, Employee Count, Credit, Contact, Address
WebAutomation LinkedIn Profile Data | Global Linkedin Employee Profiles | 500M+ Records | GDPR Compliant | Monthly Updates
Global Job Market & Job Postingd Data | 280B+ Records Updated Daily, Global Employee & Recruiting Insights
US Employee Data | Accurate Contact Information, Job Experience, LinkedIn URLs + More | Recruiting / HR
Thomson Data | Recruiting Data - Job Recruitment Data - Employee Data - Open Role Insights Data - 13M+ Companies Covered - Updated Monthly
Monetize data on Datarade Marketplace
Top Employee Data Providers & Companies
Popular Use Cases for Employee Data
Employee data is vital for enhancing workforce management and planning. Companies use it for recruitment strategies, identifying trends in skills and qualifications to attract the best talent. It supports salary benchmarking, comparing compensation across roles and industries to ensure competitiveness. Additionally, workforce planning leverages employee data to analyze demographics and predict future hiring needs, just to mention a few.
Employee Data Use Cases in Detail
HR Management
Employee data is primarily used for effective HR management within an organization. This includes various tasks such as employee onboarding, performance evaluation, training and development, compensation and benefits management, and employee engagement. By maintaining comprehensive employee data, HR departments can efficiently manage the workforce, make informed decisions, and ensure compliance with labor laws and regulations.
Payroll and Benefits Administration
Employee data is crucial for payroll and benefits administration processes. It enables accurate calculation of salaries, wages, bonuses, and deductions based on factors like attendance, leave, overtime, and tax regulations. Additionally, employee data helps in managing benefits programs such as health insurance, retirement plans, and other employee perks. This use case ensures timely and accurate compensation and benefits disbursement to employees.
Talent Acquisition and Succession Planning
Employee data plays a vital role in talent acquisition and succession planning strategies. It helps recruiters and hiring managers identify suitable candidates for job vacancies by analyzing skills, qualifications, experience, and performance records. Employee data also aids in succession planning by identifying potential candidates for key positions within the organization, ensuring a smooth transition during leadership changes or employee turnover. This use case ensures the organization has a strong talent pipeline and can effectively fill critical roles.
Types of Employee Data
Employee data typically includes various types of information that an organization collects and manages about its employees for HR and administrative purposes. These data types can vary from one organization to another, but here are some common categories of employee data:
-
Personal Information:
- Full name
- Date of birth
- Social security number (or equivalent)
- Gender
- Marital status
- Nationality or citizenship
- Contact information (address, phone number, email)
-
Employment Information:
- Job title
- Employee ID or unique identifier
- Department or team
- Date of hire
- Employment status (full-time, part-time, contract, etc.)
- Work location
- Reporting structure (supervisor, manager, etc.)
-
Compensation and Benefits:
- Salary or hourly wage
- Pay frequency (e.g., bi-weekly, monthly)
- Pay rate changes
- Bonuses and incentives
- Benefits enrollment (health insurance, retirement plans, etc.)
- Tax withholding information
-
Work History:
- Previous employment history
- Promotions and transfers
- Performance reviews
- Disciplinary actions or warnings
- Termination or resignation details
-
Time and Attendance:
- Work hours
- Attendance records
- Overtime hours
- Paid time off (vacation, sick leave, holidays)
- Timekeeping records
-
Training and Development:
- Training and certification records
- Skillset and qualifications
- Professional development history
- Training needs and plans
-
Emergency Contacts:
- Names and contact information of emergency contacts
-
Health and Medical Information:
- Health insurance details
- Disability status
- Medical leave records
- Workplace injury or illness records
-
Diversity and Inclusion:
- Race/ethnicity
- Disabilities or accommodations
- Gender identity and sexual orientation (in some cases)
-
Performance Data:
- Goals and objectives
- Performance appraisals
- Achievements and recognition
-
Employee Surveys and Feedback:
- Results of employee surveys
- Feedback and comments
- Suggestions and complaints
-
Exit Data:
- Reason for termination
- Exit interview feedback
- Return of company property
Main Attributes of Employee Data
Employee data typically includes a range of attributes that provide information about an individual employee. These attributes may include personal details such as name, age, gender, contact information, and address. Additionally, employee data often includes employment-related information such as job title, department, date of hire, salary, benefits, and performance evaluations. Other attributes that might be found in employee datasets include educational background, certifications, training records, attendance, leave history, and disciplinary actions. Here’s a table of the main attributes you might find on Employee Datasets: [Table not provided].
Attribute | Description |
---|---|
Employee ID | Unique identifier for each employee |
Name | Full name of the employee |
Gender | Gender of the employee |
Date of Birth | Date of birth of the employee |
Nationality | Nationality of the employee |
Address | Current address of the employee |
Contact Number | Contact number of the employee |
Email address of the employee | |
Department | Department in which the employee works |
Position | Job position/title of the employee |
Salary | Salary or compensation of the employee |
Employment Status | Current employment status of the employee (e.g., full-time, part-time, contract) |
Hire Date | Date when the employee was hired |
Termination Date | Date when the employee’s employment was terminated (if applicable) |
Supervisor | Name of the employee’s supervisor or manager |
Performance Rating | Performance rating or evaluation of the employee |
Training History | History of training programs or courses attended by the employee |
Leave History | History of leaves taken by the employee |
Attendance | Attendance records of the employee |
Benefits | Benefits or perks provided to the employee |
Emergency Contact | Name and contact details of the employee’s emergency contact person |
Bank Account Details | Bank account information for salary deposits |
Tax Information | Tax-related information for payroll purposes |
Work Schedule | Regular work schedule or shift timings of the employee |
Work Location | Physical location or office where the employee works |
Skills | Skills possessed by the employee |
Certifications | Professional certifications or licenses held by the employee |
Languages | Languages known or spoken by the employee |
Education | Educational qualifications of the employee |
Experience | Work experience details of the employee |
Performance History | Historical performance records or evaluations of the employee |
Disciplinary Actions | Any disciplinary actions taken against the employee |
Promotions | Details of any promotions or career advancements of the employee |
Retirement Plan | Participation in retirement plans or pension schemes |
Health Insurance | Health insurance coverage details for the employee |
Other Benefits | Additional benefits or allowances provided to the employee |
Dependents | Information about the employee’s dependents (e.g., spouse, children) |
Work Authorization | Work authorization or visa status of the employee (if applicable) |
Work Permits | Details of any work permits or licenses required for the employee’s job |
Union Membership | Membership in any labor |
How are Employee Data products priced?
Employee datasets are typically priced based on various factors such as the size of the dataset, the level of detail and accuracy of the information provided, and the source from which the data is obtained. The pricing structure may also depend on the specific requirements of the buyer, such as the industry or the purpose for which the data will be used. Additionally, the reputation and credibility of the data provider can influence the pricing. Generally, employee datasets are priced on a per-record basis or through subscription models, where buyers pay a recurring fee for access to the data. The pricing of employee datasets can vary significantly, ranging from affordable options for small businesses to more expensive packages for larger organizations with specific needs.
Frequently Asked Questions
How is Employee Data collected?
Employee data is collected through various methods, including HR information systems (HRIS), time and attendance systems, performance management systems, employee surveys, self-reporting, collaboration tools, and third-party data providers. These sources capture data on employee demographics, performance, attendance, engagement, and more, enabling organizations to analyze and utilize the information effectively.
What is Employee Data used for?
Employee data is used for workforce planning, performance management, talent acquisition, diversity initiatives, compensation management, employee engagement, and predictive analytics. By analyzing and utilizing employee data, organizations can make informed decisions, enhance productivity, drive organizational growth, and create a positive work environment.
What’s a quality checklist for Employee Data?
A quality checklist for employee data includes ensuring data accuracy, completeness, relevancy, timeliness, and consistency. It involves verifying and validating data sources, implementing data governance practices, maintaining data security and privacy, and complying with applicable data protection regulations.
How is Employee Data priced?
Employee data pricing can vary depending on factors such as data quality, quantity, depth, and the level of analysis provided. It may be priced based on a subscription model, per employee or per data point, or as part of a bundled service. Pricing structures are typically determined by data marketplace providers or data vendors based on market demand and the value of the insights derived from the data.
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