Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4MM+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

Ever wondered what REALLY drives employee turnover, performance, and retention? This power-packed dataset of 50,000 records uncovers the hidden patterns behind workforce dynamics, helping you decode the true story of hiring, leadership influence, and workplace engagement.

🔍 What’s Inside? 📅 Time-Based Analysis: Track hiring, promotions, and attrition over time. 👥 Leadership Influence: Identify which Senior Leaders drive success or struggle with retention. 📊 Performance & Productivity: Measure engagement, stress levels, job satisfaction, and training effectiveness. 💰 Hiring & Cost Efficiency: Evaluate recruitment costs, time to fill positions, and internal promotions. 🏡 Work-Life Balance: Analyze work-from-home trends, overtime, and stress levels across departments. 🎯 Retention & Risk Factors: Discover who is most at risk of leaving and why with retention risk analytics.

🔥 What Can You Do With It? ✅ Build Stunning Power BI Dashboards – Transform raw data into interactive insights. ✅ Solve Real-World HR Challenges – Use analytics to predict attrition, optimize hiring, and improve retention. ✅ Uncover Leadership Trends – Identify which leaders foster growth vs. those driving attrition. ✅ Analyze Workplace Culture – Understand how job satisfaction, training, and diversity impact engagement.

🔹 Problem 1: Attrition Analysis - Who is Leaving and Why? Scenario: Your company is experiencing a high turnover rate, and leadership wants to understand who is leaving and why.

Problem 2: Leadership Impact - Who is Retaining vs. Losing Talent? Scenario: Your company’s leadership wants to assess the effectiveness of senior leaders in retaining talent and managing high-performing teams.

Problem 3: Hiring Effectiveness - Which Sources Work Best? Scenario: HR wants to optimize the hiring process by identifying the most effective recruitment sources.

Problem 4: Workforce Diversity - Is the Organization Inclusive? Scenario: The leadership wants to understand diversity trends and whether they need to improve inclusivity in hiring.

Problem 5: Work-Life Balance - Who is Overworked? Scenario: There are concerns that some employees are working too many hours, leading to burnout and lower engagement.

Problem 6: Performance & Compensation - Are High Performers Paid Well? Scenario: The HR department suspects that high performers are not being fairly compensated.

Problem 7: Training Effectiveness - Does Training Improve Performance? Scenario: HR wants to assess whether training programs are improving employee performance and retention.

The HR analytics tools market is experiencing robust growth, driven by the increasing need for data-driven decision-making in human resource management. The market, estimated at $15 billion in 2025, is projected to achieve a compound annual growth rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, organizations are increasingly leveraging data to optimize recruitment processes, improve employee engagement, and enhance workforce planning. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enabling more sophisticated analytics capabilities, providing actionable insights into employee behavior, performance, and attrition. Thirdly, the rising adoption of cloud-based HR solutions is facilitating easier access to data and enhanced collaboration across HR teams. The market is segmented by various tools, including Python, RStudio, Tableau, KNIME, Power BI, Microsoft Excel, Orange, and Apache Hadoop, each catering to different analytical needs and organizational scale. Despite the significant growth potential, the market faces certain challenges. Data privacy and security concerns remain a major hurdle, especially given the sensitive nature of employee data. The lack of skilled professionals proficient in data analytics and HR practices also presents a limitation. Furthermore, the integration of disparate HR data sources can be complex and time-consuming. However, these challenges are being addressed through the development of robust data security protocols, specialized training programs, and integrated HR software solutions. The North American region currently holds the largest market share, but Asia-Pacific is anticipated to show the fastest growth in the coming years due to the increasing adoption of HR analytics tools in rapidly growing economies.

🟡Please Upvote my dataset If you like It.✨

This dataset contains valuable employee information over time that can be analyzed to help optimize key HR functions. Some potential use cases include:

Attrition analysis: Identify factors correlated with attrition like department, role, salary, etc. Segment high-risk employees. Predict future attrition.

Performance management: Analyze the relationship between metrics like ratings, and salary increments. recommend performance improvement programs.

Workforce planning: Forecast staffing needs based on historical hiring/turnover trends. Determine optimal recruitment strategies.

Compensation analysis: Benchmark salaries vs performance, and experience. Identify pay inequities. Inform compensation policies.

Diversity monitoring: Assess diversity metrics like gender ratio over roles, and departments. Identify underrepresented groups.

Succession planning: Identify high-potential candidates and critical roles. Predict internal promotions/replacements in advance.

Given its longitudinal employee data and multiple variables, this dataset provides rich opportunities for exploration, predictive modeling, and actionable insights. With a large sample size, it can uncover subtle patterns. Cleaning, joining with other contextual data sources can yield even deeper insights. This makes it a valuable starting point for many organizational studies and evidence-based decision-making.

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This dataset contains information about different attributes of employees from a company. It includes 1000 employee records and 12 feature columns.

The columns are:

satisfaction_level: Employee satisfaction score (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale) number_project: Number of projects employee worked on average_monthly_hours: Average hours worked in a month time_spend_company: Number of years spent with the company work_accident: If an employee had a workplace accident (yes/no) left: If an employee has left the company (yes/no) promotion_last_5years: Number of promotions in last 5 years Department: Department of the employee Salary: Annual salary of employee satisfaction_level: Employee satisfaction level (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale)

Analysis of ‘HR Data for Analytics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jacksonchou/hr-data-for-analytics on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Context

This is dataset is for HR analytics, the user who previously submitted this deleted the public dataset. The dataset contains employee profiles of a large company, where each record is an employee.

--- Original source retains full ownership of the source dataset ---

The global Human Resource (HR) Analytics market size reached USD 3.10 Billion in 2021 and is expected to reach USD 10.90 Billion in 2030 registering a CAGR of 15.0%. HR Analytics industry report classifies global market by share, trend, growth and based on component, deployment, organization size, a...

Tired of guessing what's happening in the job market? Xverum's 13M+ job data gives you real-time insights into the dynamic world of work, empowering you to make data-driven decisions and stay ahead of the curve.

Why Xverum's employee data?

➨ Real-time intelligence: Get a pulse on the job market with daily updates from over 13 million job ads, revealing the latest trends and opportunities.

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Actionable insights: Use Xverum's data to:

➨ Optimize your HR strategy: Identify in-demand skills, salary expectations, and talent pools to attract the best talent.

➨ Validate your B2B leads: Target companies actively hiring for your ideal clients, maximizing your marketing ROI.

➨ Unlock HR intelligence: Gain deeper insights into employee demographics, industry trends, and competitor hiring practices.

➨ Optimize talent acquisition: Attract the right talent with precision, ensuring your recruitment efforts are effective and efficient.

➨ Conduct in-depth labor market research: Analyze specific industries, regions, and job categories to inform your business strategies.

➨ Effortless integration: Our industry-standard CSV formats seamlessly integrate with your existing systems and tools for easy analysis.

➨ Historical data at your fingertips: Access past job trends, using 3 years of historical job data, to understand how the market has evolved and anticipate potential future opportunities.

Xverum's global HR data is your secret weapon for success in the dynamic job market. Contact us today to learn how it can transform your business!

In the diverse and evolving field of Human Resources, effective communication and targeted outreach are crucial. Solution Publishing by Allforce stands as a pioneering digital audience data tool, specifically designed to connect B2B marketers with over 2.4 million HR professionals working in Benefits, Payroll, Recruiting, Training, and more, across 475,000 companies.

Comprehensive Reach with Specific Focus Safe for you to Email - We Email Newsletters to the Data

This vast network encompasses a wide range of HR specialties, allowing you to tailor your marketing efforts to specific segments like Benefits, Payroll, Recruiting, or Training. This targeted approach ensures that your message reaches the most relevant professionals, enhancing engagement and response rates.

Direct Email Marketing: Connecting with HR Decision-Makers

Our extensive email database is curated to reach key HR decision-makers effectively. Regular updates and maintenance ensure high deliverability and engagement, allowing your messages to resonate with the intended audience in the HR community.

Telemarketing: Building Relationships with HR Professionals

Gain access to verified phone numbers of HR experts for impactful telemarketing campaigns. This direct approach fosters personal connections and meaningful conversations with HR professionals, paving the way for successful business relationships.

Digital Display Advertising: Captivating HR Audiences Online

Utilize the power of digital display advertising to capture the attention of HR professionals. Our data-driven strategies ensure that your ads reach and engage the right audience, increasing visibility and impact in the HR sector.

Postal Mail: Creating Tangible Impressions in HR

In the digital age, the physical nature of postal mail offers a unique and memorable way to connect with HR professionals. Our postal database enables you to send targeted, physical marketing materials directly to HR departments, adding a personal touch to your marketing strategy.

LinkedIn Outreach: Networking with HR Industry Leaders

Enhance your LinkedIn marketing efforts with HR Continuum. By matching our rich data with LinkedIn profiles, your team can engage HR professionals with precision. Personalized InMail messages, strategic connection requests, and relevant content help build and nurture professional relationships in the HR community.

Verification via LinkedIn URL: Maintaining Data Excellence

Each HR contact in our database is verified using their LinkedIn URL, ensuring you connect with current, active professionals in the HR field. This verification process guarantees data accuracy, relevance, and credibility in your outreach.

Our data is not just a tool, but a gateway to the heart of the HR community. With our comprehensive database and multi-channel marketing approach, you are poised to effectively reach and influence key players in the HR field, driving impactful results for your B2B marketing efforts.

This dataset titled Human Resources.csv contains anonymized employee data collected for internal HR analysis and research purposes. It includes fields such as employee ID, department, gender, age, job role, and employment status. The data can be used for workforce trend analysis, HR benchmarking, diversity studies, and training models in human resource analytics.The file is provided in CSV format (3.05 MB) and adheres to general data privacy standards, with no personally identifiable information (PII).Last updated: April 11, 2025. Uploaded by Anurag Pardiash.

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting, employee data / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

EMPLOYEE Data and Resources كشف باسماء الموظفين 20211PDF كشف باسماء الموظفين 20211 Explore More information Download

The global Human Resources (HR) Software market size was valued at USD 22.1 billion in 2022 and is projected to grow from USD 25.3 billion in 2023 to USD 51.7 billion by 2033, exhibiting a CAGR of 8.6% during the forecast period. The increasing adoption of cloud-based and on-premises HR solutions, growing focus on HR analytics and automation, and increasing demand for employee engagement and talent management solutions are key factors driving market growth. North America held the largest market share in 2022 due to the presence of a large number of established vendors and early adoption of advanced technologies. Asia Pacific is expected to witness the fastest growth during the forecast period driven by the increasing adoption of HR software solutions in emerging economies like China and India. Key players in the HR Software market include ADP, Kronos Workforce Ready, SAP, Cornerstone OnDemand, Workday, Gusto, BambooHR, and ClearCompany HRM.

APISCRAPY's Job Scraper grants access to a treasure trove of job posting data, encompassing invaluable Human Resources (HR) insights and comprehensive job datasets & Salary data. Unlock opportunities with rich data HR-related Data.

The global Human Resources Information System (HRIS) software market is experiencing robust growth, driven by increasing adoption of cloud-based solutions, the need for enhanced employee self-service capabilities, and the rising demand for data-driven HR analytics. The market, estimated at $25 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 10% through 2033, reaching an estimated $50 billion. Key drivers include the growing complexities of managing a global workforce, the need for streamlined HR processes to improve efficiency and reduce costs, and the increasing focus on employee engagement and retention. The shift towards cloud-based solutions offers scalability, accessibility, and cost-effectiveness, attracting businesses of all sizes. Furthermore, the integration of HRIS with other business applications, such as payroll and talent management systems, is fueling market expansion. Competition is fierce among established players like Sage, SAP, Oracle (NetSuite), ADP, and Workday, along with emerging innovative startups offering niche solutions. The market is segmented by deployment mode (cloud, on-premise), business size (small, medium, large), and industry vertical (healthcare, retail, manufacturing, etc.). While data security and integration challenges remain potential restraints, the overall market outlook remains positive, with continued innovation and adoption driving growth in the coming years. The competitive landscape is characterized by a mix of large established vendors and smaller, specialized providers. The larger players leverage their extensive product portfolios and global reach, while smaller companies often focus on specific niches or offer innovative features. Regional variations exist, with North America and Europe currently holding the largest market shares, but the Asia-Pacific region is exhibiting significant growth potential due to rapid economic expansion and increasing digital adoption. Future growth will be significantly influenced by advancements in artificial intelligence (AI) and machine learning (ML), enabling predictive analytics and automation of HR functions. The increasing demand for compliance with evolving data privacy regulations will also shape the market landscape, driving the need for robust security measures and compliance-focused HRIS solutions.

Analysis of ‘HR Analytics: Employee Promotion Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/arashnic/hr-ana on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Content

A large MNC have 9 broad verticals across the organisation. One of the problem is identifying the right people for promotion (only for manager position and below) and prepare them in time.

The final promotions are only announced after the evaluation and this leads to delay in transition to new roles. Hence, company needs help in identifying the eligible candidates at a particular checkpoint so that they can expedite the entire promotion cycle.

Multiple attributes have been provided around Employee's past and current performance along with demographics.

Features:

• employee_id: Unique ID for employee
• department: Department of employee
• region: Region of employment (unordered)
• education: Education Level
• gender: Gender of Employee
• recruitment_channel: Channel of recruitment for employee
• no_ of_ trainings: no of other trainings completed in previous year on soft skills, technical skills etc.
• age: Age of Employee
• previous_ year_ rating: Employee Rating for the previous year
• length_ of_ service: Length of service in years
• awards_ won?: if awards won during previous year then 1 else 0
• avg_ training_ score: Average score in current training evaluations
• is_promoted: (Target) Recommended for promotion

Inspiration

• Predict whether a potential promotee at checkpoint in the test set will be promoted or not after the evaluation process.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘HR data, Predict changing jobs (competition form)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kukuroo3/hr-data-predict-change-jobscompetition-form on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context This dataset was taken from link and separated into competition format. The label for the test data is provided in the form of a function.

--- Original source retains full ownership of the source dataset ---

The global Human Resources Information System (HRIS) software market is experiencing robust growth, driven by the increasing need for efficient talent management, enhanced employee self-service capabilities, and the rising adoption of cloud-based solutions. The market's expansion is fueled by several key factors, including the growing complexity of HR functions, the need for improved data analytics to support strategic decision-making, and the increasing pressure on organizations to optimize workforce costs. The shift towards remote work models accelerated by recent global events has further intensified the demand for flexible and accessible HRIS solutions. Large enterprises are driving a significant portion of the market due to their complex HR needs and substantial budgets for software investments. However, SMEs are also increasingly adopting HRIS solutions, recognizing their potential to improve operational efficiency and streamline HR processes. Competition is intense, with established players like SAP, Oracle (NetSuite), and Workday competing alongside smaller, specialized vendors offering niche solutions. The market is segmented by deployment model (cloud-based and on-premises) and target user (large enterprises and SMEs). Cloud-based solutions are gaining significant traction due to their scalability, cost-effectiveness, and accessibility. While on-premises solutions maintain a presence, particularly in highly regulated industries, the trend is clearly towards cloud adoption. Geographic distribution shows strong growth across North America and Europe, with emerging markets in Asia-Pacific showing promising potential for future expansion. The overall market exhibits a healthy Compound Annual Growth Rate (CAGR), indicating sustained growth prospects throughout the forecast period. The future of the HRIS software market hinges on technological advancements, such as the integration of artificial intelligence (AI) for talent acquisition and performance management, and the increasing use of machine learning for predictive analytics. Furthermore, the increasing demand for enhanced security features to protect sensitive employee data will continue to shape the market landscape. The integration of HRIS with other enterprise resource planning (ERP) systems is also a key trend, fostering greater data integration and improving overall business efficiency. Potential restraints include the high initial investment costs associated with implementing some HRIS solutions, the need for ongoing maintenance and support, and the complexities involved in data migration and integration. Nevertheless, the long-term prospects for the HRIS software market remain positive, driven by continued technological innovation and the persistent need for organizations to optimize their human capital management strategies. Considering the market's current trajectory and anticipated trends, we can project sustained growth for the foreseeable future.

Human resources and benefits administration companies have experienced significant turbulence recently due to shifting economic conditions. COVID-19 initially caused a dramatic slowdown in many sectors, which forced numerous companies to cut back on discretionary spending systems, including HR services, as organizations downscaled operations and pivoted to internal HR solutions. In 2020, this resulted in a slight revenue decline, though federal interventions like the Paycheck Protection Program (PPP) partially mitigated potential financial stressors. Afterward, as the economic recovery commenced and unemployment figures dwindled to more consistent levels, corporations slowly began reintegrating HR and benefits services into their business models, supporting a notable revenue rebound in 2022. Beginning in 2022, higher interest rates and increasing fears of an economic recession dampened corporate enthusiasm for external HR expenditure, resulting in falling revenue in 2023 and 2024. Despite these hindrances, the past five years also saw rapid technological advancements and increased adoption of AI and machine learning solutions, enabling service providers to innovate their offerings and gain a competitive edge in a saturated market. Concurrently, market share concentration has declined as more companies have entered the industry in expectation of rising revenue streams in the near future. This has bolstered internal competition, putting downward pressure on profit. Overall, revenue for human resources and benefits administration companies has inched upward at a CAGR of 1.0% over the past five years, reaching $88.9 billion in 2025. This includes a 0.5% decline in revenue in that year. Looking ahead, providers anticipate a more optimistic trajectory. As GDP growth maintains a steady pace, generating more employment opportunities, demand for comprehensive HR services will likely see an upturn. Economic uncertainty remains due to tariffs being recently implemented, which may affect GDP growth and corporations' performance. While substitute competition becomes more prevalent due to the increased attractiveness of internal HR services, cloud-based solutions will become essential. Demand for wellness and diversity, equity and inclusion (DEI) initiatives will also swell, requiring providers to adapt to these trends for competitive advantage. Overall, revenue for human resources and benefits administration businesses is forecast to mount at a CAGR of 2.3% over the next five years, reaching $99.8 billion in 2030.

Analysis of ‘HR Analytics: Job Change of Data Scientists’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/arashnic/hr-analytics-job-change-of-data-scientists on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context and Content

A company which is active in Big Data and Data Science wants to hire data scientists among people who successfully pass some courses which conduct by the company. Many people signup for their training. Company wants to know which of these candidates are really wants to work for the company after training or looking for a new employment because it helps to reduce the cost and time as well as the quality of training or planning the courses and categorization of candidates. Information related to demographics, education, experience are in hands from candidates signup and enrollment.

This dataset designed to understand the factors that lead a person to leave current job for HR researches too. By model(s) that uses the current credentials,demographics,experience data you will predict the probability of a candidate to look for a new job or will work for the company, as well as interpreting affected factors on employee decision.

The whole data divided to train and test . Target isn't included in test but the test target values data file is in hands for related tasks. A sample submission correspond to enrollee_id of test set provided too with columns : enrollee _id , target

Note: - The dataset is imbalanced. - Most features are categorical (Nominal, Ordinal, Binary), some with high cardinality. - Missing imputation can be a part of your pipeline as well.

# Features #
- enrollee_id : Unique ID for candidate

• city: City code

• city_ development _index : Developement index of the city (scaled)

• gender: Gender of candidate

• relevent_experience: Relevant experience of candidate

• enrolled_university: Type of University course enrolled if any

• education_level: Education level of candidate

• major_discipline :Education major discipline of candidate

• experience: Candidate total experience in years

• company_size: No of employees in current employer's company

• company_type : Type of current employer

• last_new_job: Difference in years between previous job and current job

• training_hours: training hours completed

• target: 0 – Not looking for job change, 1 – Looking for a job change

Inspiration

• Predict the probability of a candidate will work for the company
• Interpret model(s) such a way that illustrate which features affect candidate decision # Please refer to the following task for more details: https://www.kaggle.com/arashnic/hr-analytics-job-change-of-data-scientists/tasks?taskId=3015

--- Original source retains full ownership of the source dataset ---

The main area of human resources (HR) for large organizations worldwide that are planning to increase their staff is HR data analytics, with 34 percent of respondents in a 2019 survey stating they plan to increase their staffing in this role.