🛒 Superstore Sales Analysis (SQLite + SQL)

Overview

A compact SQL portfolio project on the classic Sample Superstore dataset.
Goal: identify top customers, profitable products/segments, regional performance, time trends, and the impact of discounts on margins.

Dataset

• Source: sample_superstore.csv (public Superstore sample)
• Size: ~10k rows (your import may vary slightly)
• Date range: <fill after running> e.g., 2014-10-10 → 2017-12-30
• Target table: superstore (built by setup_superstore.sql)
• Key columns: OrderDate (YYYY-MM-DD), Sales (REAL), Profit (REAL), Discount (0–1), Category, SubCategory, Segment, Region, CustomerName, ProductName, ...

How to reproduce

# Build/refresh the SQLite DB and load the CSV (CLI is required for .mode/.import)
sqlite3 superstore.db ".read setup_superstore.sql"

# Run analysis queries in VS Code with SQLTools:
# open queries.sql → select a statement → Ctrl+E, Ctrl+E