- People struggle to find events they want to attend.
- Reliable ticket purchase links are often hard to locate.
- Companies spend millions on ads, while cost per click keeps rising.
- A structured PostgreSQL database that centralizes events, categories, and companies.
- Each event includes a verified ticket link.
- Queries allow filtering down to almost personalized event lists.
- Click tracking provides organic engagement insights, reducing reliance on expensive ads.
A PostgreSQL project that makes event discovery easy and trustworthy for users, while giving companies actionable insights to cut advertising costs.
- PostgreSQL relational database
- SQL (DDL, DML, BI queries)
- Schema evolution with
ALTER TABLE - Performance optimization with constraints, indexes, and views
- Event discovery with filters by category, city, and year
- Verified ticket links for trustworthy purchases
- Personalized lists through advanced queries
- Click tracking to measure popularity
- Company insights with BI reports
- Schema design → tables for companies, categories, events
- Data population → realistic inserts with event names and ticket links
- Schema evolution → alters and updates for new needs
- Analytics → BI queries for insights
- Enhancements → constraints, indexes, views
- Designing normalized schemas
- Maintaining data integrity with constraints
- Using SQL for business intelligence
- Organizing a GitHub repo professionally
This project helped me grow from basic SQL into building a mini data platform that solves real problems for both users and companies.
- Stored procedures for automation
- Dashboards with BI tools
- Recommendation system based on user preferences
- Revenue tracking integrating ticket sales data
- Adding a user‑friendly front end