This project focuses on analyzing and visualizing key workforce metrics from the Human Resources Data Set. It leverages advanced Excel techniques such as Power Query, Pivot Tables, statistical analysis, and various lookup functions to extract, clean, and model HR data. The ultimate goal is to gain insights into workforce diversity, employee performance, and organizational trends to guide HR decision-making and strategic workforce planning.
GitHub - mdntarif/Human-Resources-Data-Analysis
This analysis uses a dataset with multiple tables containing employee information, performance scores, and HR-related data. The project solves business problems related to employee demographics, performance evaluations, workforce diversity, engagement, and organizational structure. Key techniques include Power Query, statistical analysis (mean, median, mode, variance, etc.), and data visualization through Pivot Tables and charts.
Key Business Problems & Solutions
Workforce Diversity and Engagement:
Analyze gender, race, and age distribution by department and calculate average engagement scores using COUNTIF and AVERAGEIF. Visualize with charts.
Employee Profile & Communication:
Extract and clean employee data, generate personalized email addresses with standardized format (initial + last name + age).
Performance Evaluation:
Use VLOOKUP, XLOOKUP, and INDEX-MATCH to retrieve employee names and performance scores. Automate performance evaluation reporting.
Employee Distribution Analysis:
Use Pivot Tables to compare salary and performance ratings across categories, segmented by marital status.
Department-Wise Employee Comparison:
Analyze employee distribution by department, gender, and marital status using Pivot Tables.
Engagement and Satisfaction:
Calculate average engagement and satisfaction scores by department, filtered by gender. Visualize trends with Clustered Column Charts.
Position and Compensation Analysis:
Compare employee positions, engagement scores, and pay rates across departments, filtering by marital status, citizenship, and gender.
Statistical Insights for Talent Management:
Apply statistical concepts (mean, median, variance, etc.) to uncover insights like average age, common departments, and correlations for strategic HR decisions.