Project Overview

This project focuses on analyzing a large dataset of job postings to uncover trends in the data analytics job market. Using SQL as the primary tool, I performed data cleaning, transformation, and exploratory analysis to identify insights related to high-demand skills, salary ranges, job locations, and employer requirements. The goal was to structure the raw data into meaningful outputs that support career decision-making, workforce planning, and market intelligence.

Objective

To transform a messy, multi-table dataset into a clean, analysis-ready environment and extract insights that answer key questions, such as:

Which skills are most in demand for data roles?

How do salaries vary by job title and location?

What job categories show the fastest growth?

Which companies are hiring most aggressively?

Technical Approach

I used SQL extensively to streamline the dataset and uncover insights through a combination of:

Data Cleaning: handling duplicates, missing values, improper data types, and inconsistent formatting.

Data Transformation: creating lookup tables, applying joins, building summary tables, and standardizing fields for downstream analysis.

Exploratory Queries: using window functions, aggregations, subqueries, and CTEs to extract trends and performance indicators.

Business Logic Modeling: designing relationships between job skills, job titles, seniority, employer type, and salary expectations.

This structured analytical workflow allowed me to build a reliable dataset that supports deeper modeling and dashboarding.

Key Insights

Some of the insights generated from the SQL analysis include:

SQL, Python, and Power BI consistently rank as top skills across most data roles.

Hybrid and remote roles show higher salary ranges compared to strictly onsite listings.

Senior-level roles emphasize cloud technologies and advanced analytics tools.

Companies hiring for analytics roles tend to cluster in tech, finance, and consulting sectors.

Impact

The insights from this project help:

Job seekers understand the competitive landscape

Recruiters refine job descriptions and skill requirements

Businesses identify skill gaps and hiring opportunities

Analysts (like myself) stay aligned with market expectations

GitHub Repository

Full project files, SQL scripts, and documentation can be found here:
🔗 https://github.com/iyanusol/SQL-Project-Analysis