🗓️ Task 4: SQL for Data Analysis

🧰 Tools Used

• MySQL Workbench 8.0
• Northwind Dataset (Customized, CSV files imported manually)
• Manual Table Creation and Constraints
• SQL Querying for Business Insights

🧱 Database: northwind_internship

✅ Tables Created

1. categories
2. customers
3. orders
4. employees
5. products
6. shippers
7. orderDetails

All tables were created with appropriate data types, primary keys, and foreign key constraints to maintain referential integrity.

🔍 SQL Skills Demonstrated

✅ Core Concepts

• SELECT, WHERE, ORDER BY, GROUP BY
• Aggregate functions: SUM, COUNT, AVG
• Filtering: LIKE, BETWEEN
• INNER JOIN, LEFT JOIN, SELF JOIN
• LIMIT, ALIASING, ROUND
• Foreign key relationships

📑 Queries Executed

#	Query Description
1	Filter customers from Germany
2	Show employees with their reporting manager
3	Count of customers grouped by country
4	Top 5 most expensive products
5	Customer count by country
6	Discontinued products with category
7	Top 5 customers by total orders
8	Average unit price per category
9	Orders count per country
10	Top 3 most ordered products
💎 Bonus 1	Top 3 shippers by freight and order volume
💎 Bonus 2	Employee reporting hierarchy

📁 Deliverables

• Elevate_Labs_Day4.sql – Full SQL file with table creation and queries
• Elevate_Labs_Day4.pdf – Printable PDF version of SQL script
• 12+ Screenshots – Each titled and organized based on query/task
• Screenshots.pdf - Each screenshot arranged query wise

🚀 Outcome

This task strengthened my ability to:

• Design relational schemas manually
• Apply SQL joins and aggregations to extract business insights
• Handle real-world datasets with integrity
• Follow best practices in query organization and output documentation

Dataset🔗 https://www.kaggle.com/datasets/jeetahirwar/northwind-traders

Click on Screenshots.pdf to view all the screenshots 🖼️.

Author :

SALOORA VAIBHAV