Human Resources Data Analysis by Excel Power Query

The HR dataset under examination comprises two primary tables: the Employee table, offering intricate details about each employee’s background, and the Absenteeism table, documenting instances and reasons for employee absence. The synergy of these tables, facilitated by Excel’s Power Query, Index, and Match functions, provides a panoramic view of the data, empowering the exploration of correlations across diverse columns.

Recommendations:

Age-Specific Focus: Analyzing the data with Excel’s Max, Min, Average, and Standard Deviation functions reveals a propensity for absenteeism among employees aged 28 and 38. HR should exercise additional scrutiny during recruitment within this age bracket, ensuring a comprehensive evaluation of cultural fit and identifying potential contributors to absenteeism.

Commute Optimization: With an average commuting distance of 27.1 kilometers, HR should explore strategies to mitigate challenges. This may involve offering flexible work arrangements or investigating transportation solutions to enhance work-life balance and reduce employee stress.

Absenteeism Management: The identification of Ramy as the employee with the highest absenteeism emphasizes the necessity for targeted support and intervention. HR initiatives such as employee assistance programs, health initiatives, or flexible scheduling options can aid in addressing and mitigating absenteeism concerns.