SQL AdventureWorks Analysis

Advanced T-SQL Querying and Data Relationship Mapping

The SQL AdventureWorks Analysis project is a comprehensive deep-dive into the relational logic of one of the industry’s most complex sample databases. It bridges the gap between raw data storage and actionable business intelligence.

Rather than just listing queries, this project focuses on solving multi-layered business problems—ranging from sales performance tracking to inventory management—using optimized T-SQL scripts.

🚀 Explore Queries & Scripts on GitHub

Project Highlights

This repository demonstrates mastery over the essential pillars of relational database management:

  • Complex Joins: Architecting relationships across Production, Sales, and Person schemas to create unified datasets.
  • Analytical Aggregations: Leveraging window functions and grouping to extract KPIs like Year-over-Year growth and regional sales density.
  • Modular Design: Utilizing Views and Subqueries to create reusable, clean, and maintainable code blocks.
  • Data Integrity: Implementing Update and Delete protocols while maintaining referential integrity.

📂 Repository Structure

The queries are organized into logical modules based on SQL operations:

Directory Description
Aggregation Summary statistics using GROUP BY, SUM, AVG, and HAVING clauses.
Join Multi-table relational queries using INNER, LEFT, and CROSS JOINS.
SubQuery Complex data filtering using nested queries and correlated subqueries.
Views Implementation of virtual tables for simplified data access and security.
Update & Delete Data manipulation scripts for maintaining database integrity.

Technologies used: T-SQL, SQL Server, SSMS, Relational Algebra.