🔹 Overview

This project explores AdventureWorks sample database with multiple exercises covering purchasing, sales, HR, and person/address data. The goal was to practice SQL joins, unions, case logic, derived columns, and date functions in real-world-like scenarios.

🔹 Skills Demonstrated

Joins (INNER, LEFT, RIGHT) across multiple schemas (Purchasing, Sales, Person, HR)

CASE statements for conditional derived columns

ISNULL() handling for missing values

UNION ALL to combine structurally similar tables

Date functions (EOMONTH, DATEDIFF, MONTH) for dynamic calculations

🔹 Key Exercises

Purchasing Orders – Categorized order sizes and enriched with Product hierarchy.

Sales vs Purchasing – Combined datasets into a unified schema using UNION ALL.

People & Addresses – Built conditional full names and applied postal code filters.

Employees & Job Categories – Derived JobCategory dynamically from JobTitle.

Dynamic Date Calculation – Found days remaining in the current month.

🔹 Insights

CASE logic allows creation of business-friendly derived attributes such as order categories and job categories.

Data standardization between Sales and Purchasing tables enables direct comparisons via UNION.

Null handling with ISNULL ensures clean and user-friendly outputs.