Aspiring Data Analyst | Data Cleaning • Google Sheets • SQL
In this project, I used SQL to analyze sales data and evaluate revenue performance across customers, cities, and products. The goal was to transform raw transactional data into meaningful insights that support data-driven decision-making.
Queried and explored the dataset using SELECT statements
Created a calculated field for total revenue using quantity and unit price
Used GROUP BY and aggregation functions (SUM) to analyze revenue patterns
Organized results to clearly identify top-performing customers, cities, and products
Jane Smith is the highest-value customer, generating the most revenue
Los Angeles is the top-performing city
Pizza and Salad are the leading revenue-generating products
SQL Data Querying (SELECT, WHERE)
Data Aggregation (SUM, GROUP BY, ORDER BY)
Calculated Fields and Data Transformation
Business Insight Generation
Analyzed sales data using SQL to calculate revenue and identify top-performing customers, cities, and products.