This repository contains a collection of SQL projects designed to demonstrate data querying, analysis, and database management across various domains, including retail, healthcare, hospitality, and HR analytics. Each project includes SQL scripts, datasets (where applicable), and documentation for hands-on learning.

• Focus: Database management for tracking assets.
• Skills: CRUD operations, reporting, and maintenance queries.

• Focus: Analyzing COVID-19 case trends, recoveries, and deaths.
• Skills: Aggregation, time-series analysis, and filtering.

• Focus: Booking trends, cancellations, and revenue optimization.
• Skills: Joins, subqueries, and revenue calculations.

• Focus: Combining datasets from multiple streaming platforms.
• Skills: Schema integration, complex joins, and data reconciliation.

• Focus: Analyzing user navigation and viewing habits.
• Skills: Behavioral pattern extraction and filtering.

• Focus: Sales performance, inventory, and customer segmentation.
• Skills: Grouping, window functions, and metrics calculation.

• Focus: Advanced retail analytics (e.g., market basket analysis).
• Skills: CTEs, stored procedures, and predictive queries.

• Focus: Library operations like loans, returns, and user activity.
• Skills: Transaction management and reporting.

• Focus: E-commerce sales and HR employee data analysis.
• Skills: Multi-table joins, pivot queries, and performance metrics.

• SQL Dialects: MySQL, PostgreSQL, SQLite, or SQL Server.
• Tools: DBeaver, pgAdmin, MySQL Workbench, or VS Code + SQL extensions.
• Optional Integration: Python (Pandas, SQLAlchemy) or Power BI for visualization.

1. Clone the Repository:

   git clone [repository-url]  

2. Set Up a Database:
   • Import provided .sql or .csv files into your SQL environment.
3. Run Queries:
   • Execute scripts in the order specified in project READMEs.

✔ Data Retrieval: SELECT, WHERE, DISTINCT
✔ Joins: INNER, LEFT, SELF joins
✔ Aggregation: GROUP BY, HAVING, SUM()/AVG()
✔ Advanced Queries: Subqueries, CTEs, Window Functions (OVER())
✔ Database Management: Indexing, constraints, and optimization.

• Add New Projects: Include SQL scripts, datasets, and a dedicated README.md.
• Improve Queries: Optimize existing scripts with comments.
• Report Issues: Flag bugs or dataset inconsistencies.

Happy Querying! 🎯

🔗 For detailed project instructions, navigate to each subfolder’s README.md.