🎓 College Placement Analytics — SQL Project

A end-to-end SQL analytics project built on simulated placement data from an engineering college.
Covers schema design, data modeling, and 14 business-focused queries using core and advanced MySQL features.

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📌 Problem Statement

Training & Placement Officers (TPOs) deal with placement data scattered across spreadsheets. This project models that data into a relational database and answers real questions about placement outcomes, salary trends, company behaviour, and student eligibility — the kind of insights that drive smarter placement strategy.

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🗃️ Database Schema

departments ──< students ──< placements >── job_roles >── companies

Table	Description
departments	Engineering branches with seat count
students	Student profiles — CGPA, batch, backlogs, gender
companies	Recruiting companies with sector and tier classification
job_roles	Roles offered — CTC, eligibility criteria, type
placements	Core fact table linking students to offers

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📊 Analysis Queries (14 Total)

#	Query	Concept Used
1	Department-wise placement rate	GROUP BY, LEFT JOIN, aggregation
2	Avg / Max / Min CTC per department	Multi-table joins, aggregation
3	Top 5 highest-paying placements	ORDER BY, LIMIT
4	Company-wise offer count & avg CTC	GROUP BY, aggregation
5	CGPA bucket vs placement outcome	CASE WHEN, conditional aggregation
6	Dream offer rate by department	Boolean SUM, percentage calculation
7	Gender-wise placement breakdown	GROUP BY gender
8	Sector-wise hiring trends	JOIN across 3 tables
9	Year-over-year placement comparison	Batch-level aggregation
10	Backlog impact on placement	CASE WHEN, LEFT JOIN
11	Unplaced students list	NOT IN subquery
12	Monthly placement trend (cumulative)	Window function: SUM OVER
13	Rank students by CTC within dept	Window function: RANK() PARTITION BY
14	Companies that return every year	GROUP_CONCAT, HAVING

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🛠️ Tech Stack

• Database: MySQL 8.0+
• Concepts: DDL, DML, Joins, Subqueries, CASE WHEN, Window Functions, Aggregations

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🚀 How to Run

# 1. Open MySQL and run schema + data
mysql -u root -p < 01_schema_and_data.sql

# 2. Run analysis queries
mysql -u root -p placement_analytics < 02_analysis_queries.sql

Or paste files directly into MySQL Workbench and execute.

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💡 Key Insights from the Data

• AI & DS and CE branches show the highest dream offer (CTC ≥ 8 LPA) rates
• CGPA above 8.0 strongly correlates with both placement rate and CTC
• Students with 2+ backlogs have significantly lower placement outcomes
• BFSI and Product sector companies offer the highest average packages
• Goldman Sachs and Razorpay represent the top-paying recruiters on campus

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📁 File Structure

college-placement-analytics/
├── 01_schema_and_data.sql    # Table creation + sample data
├── 02_analysis_queries.sql   # 14 analytical queries
└── README.md

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🙋 Author

Mansi Basutkar
B.Tech Computer Engineering | Walchand Institute of Technology, Solapur
LinkedIn | GitHub