Workforce & Salary Analytics

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Data-analytics case study built on the MySQL employees sample database, combining SQL querying with Python (pandas) modeling to answer real HR business questions: gender equality, a 20% payroll reduction, and a capped year-end bonus plan. Completed as project of the Big Data & AI Bootcamp.

Overview

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A company (framed as an Aramco-style enterprise) needs data-driven answers to three workforce questions. Working from a relational employee database, this project uses SQL to extract and aggregate the workforce data, then pandas to model and compare payroll scenarios. The result is a defensible, numbers-backed recommendation for each case.

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The work is organized as three connected case studies:

Case Study	Business Question
Gender Equality	How are male/female employees distributed across departments, titles, and pay?
Payroll Reduction	How can the company cut its annual salary spend by ~20% as fairly as possible?
Bonus Plan	How should a year-end bonus pool (capped at $50M) be distributed?

Technologies Used

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• MySQL 8
• Python 3
• Pandas
• NumPy
• Jupyter Notebook (Google Colab)
• Microsoft Excel
• Power BI

Key Findings

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• Assessed gender equality across the organization using workforce and salary data.
• Developed and compared payroll reduction scenarios to achieve a 20% cost-saving target.
• Created a bonus allocation strategy that distributed a $50M budget while meeting defined business criteria.

Screenshots

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Gender Equality Strategy

Payroll Reduction Scenarios

Bonus Allocation Results

Team Members

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• Eman Alamari
• Maha Alhazzani
• Reema Alaswad
• Raghad Aleisa
• Aljohara Alkanhal