Using SQL for Real-Life Decision Making: A Beginner's Analysis of E-Commerce Sales Data

This research explores how beginner data analysts can use SQL to generate actionable business insights in the e-commerce domain. Using a structured sample dataset of product sales, customer reviews, and geographic information, the study demonstrates SQL techniques such as aggregate functions, grouping, joins, and date-based analysis to evaluate performance across products, categories, seasons, and regions. Key analyses include identifying top-selling products, high-margin “hidden gold” items, slow-moving inventory, customer rating patterns, repeat purchase behavior, and geographic revenue distribution. A consolidated “CEO Dashboard” query illustrates how SQL can provide high-level business metrics in a single view. This study emphasizes SQL’s practical value as a decision-support tool that transforms raw transactional data into insights that inform inventory, marketing, and product strategies.