This project explores a fictional e-commerce dataset using SQL and PostgreSQL to uncover key business insights. The goal was to simulate a real-world business case where sales, customer behavior, and country performance needed to be analyzed to support data-driven decision-making. The dataset includes order-level details like products, prices, quantities, countries, and order dates across multiple months.

Using structured queries, I extracted valuable metrics, including monthly revenue, top-selling products, customer behavior patterns, and average order value. This project demonstrates my ability to work with relational databases, write clean SQL, and think analytically from a business perspective.

PostgreSQL – Used as the relational database to create, populate, and query the e-commerce dataset.

pgAdmin 4 – GUI client for PostgreSQL used to manage tables, run queries, and inspect results.

SQL – Used to analyze the data: aggregations, window functions, filtering, and sorting.

Notepad – Used to save and organize .sql scripts in a clean and reusable format.

Tableau Public - Data visualization and dashboard building

This project aims to uncover insights from a mock e-commerce dataset to support decision-making around sales performance, customer behavior, and market strategy. The key questions include:

What is the monthly revenue trend? Goal: Understand seasonality and sales performance over time.

What are the top-selling products? Goal: Identify bestsellers to inform inventory planning and marketing focus.

Which countries generate the most revenue? Goal: Recognize key markets and target future campaigns geographically.

What is the average order value? Goal: Evaluate customer spend behavior to inform upselling strategies.

What are the most common order statuses? Goal: Monitor operational performance and fulfillment efficiency.

How does AOV differ by country? Goal: Compare customer value across regions to tailor pricing or promotions.

How frequently do customers reorder? Goal: Gain insight into customer retention and lifecycle patterns.

Monthly Revenue Trend: Revenue peaked in September 2025 with 549.98 generated. Making it the highest performing month in the dataset. Q4 showed a fluctuation in November revenue, which took a dip but maintained a moderate average revenue.

Top-Selling Products:

Mechanical Keyboard – 3 units HD Webcam – 3 units Bluetooth Headphones – 2 units

Suggest strong demand for ergonomic and productivity-enhancing accessories, which may inform future inventory decisions and marketing focus.

The revenue breakdown by country reveals that:

The USA leads with the highest total revenue of $861.91, making it the most valuable market.

Canada follows with $462.46, also showing strong customer activity.

Marketing strategies should prioritize the U.S. and Canadian markets, while Australia and the U.K. may benefit from specific target campaigns.

Average order value across all transactions is $111.30, average customer spends over $100 per purchase. This is strong and will present opportunities and strategies for bundling strategies, if desired.

Translating business questions into actionable SQL queries

Using window functions and aggregation for advanced metrics

Visualizing multi-dimensional data for non-technical audiences

Dashboard design and storytelling in Tableau

End-to-end project delivery from database to insight