SQL Orders Management Project

Mastering SELECT and WHERE Statements Through a Real-World Scenario

Table of contents

• Project Overview
• What I practiced
• Database Structure
• Data Cleaning Tasks
• Client Questions Answered
• Key Learnings

Project Overview

This project simulates a small business tracking customer orders. I tracked the order flow for a company using only SELECT and WHERE statements to practice applying theory to real-world tasks.

The goal was:

• Build confidence writing SQL independently
• Learn how to think like an analyst
• Practice data cleaning and querying with limited tools.
• Use simple SQL to answer “client-style” questions.

What I Practiced

This project helped me master:

• Creating tables using CREATE TABLE
• Inserting values using INSERT INTO
• Cleaning inconsistent entries using only SELECT + WHERE
• Using REPLACE, CASE, and filtering logic
• Handling NULL values
• Writing queries to answer business questions.
• Calculating date differences with DATEDIFF

Database Structure

The ORDERS table contains: Order_id, price, status, item, delivery_city, customer_name, order_date, delivery_date.

Data Cleaning Tasks

All cleaning was done using SELECT + WHERE only. I Cleaned:

• Inconsistent city names (lagos, Lagos, ABUJA, abj)

• Status variations (Pending, pending, Delivered, delivered)

• NULL values in amount and delivery date

• Conditional replacements using CASE Example cleaning snippet: SELECT order_id, item, status, delivery_city, customer_name, price, order_date, delivery_date,

  CASE WHEN LOWER(delivery_city) = 'lagos' THEN 'Lagos' WHEN LOWER(delivery_city) IN ('abuja', 'abj') THEN 'Abuja' ELSE delivery_city END AS cleaned_city, CASE WHEN LOWER(status) = 'delivered' THEN 'Delivered' WHEN LOWER(status) = 'pending' THEN 'Pending' ELSE status END AS cleaned_status, REPLACE(item, '_', ' ') AS cleaned_item FROM orders;

Client Questions Answered

Some of the business questions solved:

Q1: Find all orders delivered late (delivery took more than 4 days).

Q2: Find all orders that were not delivered (delivery date is NULL).

Q3: List all orders from Lagos (case-insensitive).

Q4: Find all orders where the price is missing or not a valid number.

Q5: Retrieve all orders for “Power Bank” items (take note of inconsistent naming).

Example query: SELECT * FROM [dbo].[ORDERS] WHERE DATEDIFF(DAY, order_date, delivery_date) > 4;

Key Learnings

• SQL is easier when approached with real-life scenarios.
• SELECT + WHERE alone can solve a surprising number of problems.
• Small projects build confidence faster than long tutorials