HR Data Analysis Project
I analyzed the dataset of an HR department in a certain company. This is fictional data that was provided by FestMan Learning Hub. The main object of the analysis is to highlight the Employees and Salary Structure of the company.
Microsoft Excel was the only tool used for this analysis and Visualization
Data Structure and Data Cleaning
The dataset contained 742 rows and 7 columns. The columns include Employee Name, Department of Employee, Hire Date, Employment Type, Benefit Type, Salary, and Employee Rating. This is the records of employees from 2004 to 2019. I did not do much data cleaning since the data was already cleaned; I just extracted a Year column from the Hire Date using the function “Year”.
Analysis and Insights
I used only Excel functions and Formulae for the whole Analysis. Functions used include Sum, Sumifs, Count, Countifs, and Averageifs.
The Total Salary/compensation that has been paid to the employees from 2004 to 2019 is 47,928,375.
From 2004 to 2019 there have been 741 employees employed in the company which include both males and females.
The Average Salary of an employee stood at 64,681
Out of the total of 741 employees, 374 were Full Time, 126 were contracted, 120 were Half-Time and 121 were Hourly Employees.
There were 21 departments, and these were the top 10 departments with the highest number of Staff
These were the top 10 departments with the highest average salary, employees in the Environmental Compliance and Manufacturing Admin received the highest average salaries.
Employees on Full Time received more than 50% of the total salary paid which amounted to 34,544,280.
This the trend of the number of Staff the company employed from 2004 to 2019. The years 2013 and 2016 recorded the highest number of employees while 2004 and 2019 recorded the least number of employees.
Data Visualization with Excel ( A single Dashboard for all the visuals)
Recommendations
· The benefits package of the benefit types “DR” and “D” should be revised to attract more employees
· From 2016 to 2019, there was a massive drop in the number of employees in the company. A root cause analysis should be done to investigate why the sudden drop in the number of employees.