1. Install PostgreSQL

PostgreSQL is a free, open-source SQL database that's widely used in the industry.

Download it from: https://www.postgresql.org/download/

During installation, make note of:

• Your username (default is usually postgres)
• Your password
• The port number (default is 5432)

Windows: Run the installer and follow the setup wizard. Make sure to add PostgreSQL to your system PATH during installation.

Mac: Download the installer from the PostgreSQL website and follow the setup wizard.

2. Install a SQL Client

You'll need a tool to interact with your PostgreSQL database. Two good, free options:

3. Create a New Database

After launching your client and connecting to the server:

Create a new database to hold your project data. Example:

CREATE DATABASE sql_project;

4. Import Your Dataset

If your data is in a CSV file, you'll need to:

Create a table with the right column types:

CREATE TABLE my_table (
    column1 TEXT,
    column2 INT,
    column3 DATE
);

Import the data:

• In pgAdmin: Right-click the table → Import/Export → Choose your CSV file
• In DBeaver: Right-click the table → Import Data → Follow the wizard

5. Verify Your Data

Run a quick check to make sure the data loaded correctly:

SELECT * FROM my_table LIMIT 10;

6. Organize Your Project Files

Create a folder for your project that includes:

• The raw data file (CSV)
• A .sql file with your setup and queries
• A README or notes file describing your process

7. Ready for Analysis

With your data loaded and environment set up, you're ready to begin exploring, cleaning, and analyzing the data. The next section will walk you through choosing a project idea and breaking it down step by step.

Project Overview

In this project, you'll analyze real-world e-commerce sales data to uncover basic trends and performance metrics. You'll practice foundational SQL skills to summarize and clean the dataset.

Learning Objectives

• Practice writing basic SQL queries using SELECT, FROM, and WHERE
• Learn how to clean and filter data using logical operators and keywords
• Aggregate and summarize data using common SQL functions
• Gain confidence exploring real-world datasets with simple analysis

Practice Questions

Here are some beginner-friendly questions to get you started:

• How many total rows (sales records) are in the dataset?
• What is the total revenue generated across all sales?
• Which product category had the highest total quantity sold?
• What is the average sales amount per transaction?
• How many unique SKUs were sold?
• What are the top 5 most sold SKUs based on quantity?
• Which month had the highest total sales revenue?
• How many sales were B2B transactions vs non-B2B?
• Which fulfilment method was used most frequently?
• How many sales were made for each product size?

Ready to get started?

Simply download the dataset AmazonSaleReport.csv below and upload it to your PostgreSQL database.