This project performs large-scale SQL analysis on workforce compensation data to uncover salary trends, high-demand skills, and role-based compensation patterns. The objective is to generate data-driven insights to support strategic hiring and workforce planning decisions.
Organizations require structured compensation insights to:
- Benchmark salary ranges across roles
- Identify high-demand technical skills
- Support strategic talent acquisition planning
- Optimize compensation structures
This project simulates enterprise-level workforce analytics using structured SQL queries on large datasets.
- Structured workforce dataset
- 100,000+ records (simulated large-scale data)
- Fields include: role, experience level, salary, region, skills, employment type
- SQL (MySQL / PostgreSQL compatible)
- Aggregations & Window Functions
- Grouping & Ranking
- Query Optimization Techniques
- Data cleaning and validation
- Salary aggregation by role and experience
- Skill frequency analysis
- Regional compensation comparison
- Use of indexed columns for query optimization
- Ranking roles using window functions
- Identified top 10 highest-paying technical roles
- Determined most in-demand technical skills
- Analyzed salary progression by experience level
- Compared regional compensation differences
- Optimized query performance using indexing