Amazon Sales Data Analysis
Project 1: Analyze Amazon Sales Data
Project Overview
In this SQL project from InterviewMaster.ai, I practiced creating a database and a table using pgAdmin 4 and imported a csv file. I then viewed the data and had to clean several columns of data. After the data was ready to work with, I began analyzing real-world e-commerce sales data to uncover basic trends and performance metrics. I used foundational SQL skills to summarize and clean the dataset.
Data Source: Kaggle Dataset, found here
Learning Objectives
- Practice writing basic SQL queries using SELECT, FROM, and WHERE
- Practice cleaning and filtering data
- Aggregate and summarize data using common SQL functions
- Gain confidence exploring real-world datasets with simple analysis
Practice Questions
- 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 fulfillment method was used most frequently?
- How many sales were made for each product size?