SQL-based analysis of retail store inventory data to extract meaningful business insights, track stock performance, and improve inventory decision-making.

End-to-end SQL analytics project on a retail bike store dataset using PostgreSQL. Includes KPIs, AOV trends, store performance, product & brand insights, RFM customer analysis, and inventory vs sales evaluation.

Developed a retail store database and performed sales and inventory analysis using SQL. Created tables for products, suppliers, inventory, and sales, inserted sample data, and executed analytical queries to calculate revenue, profit, top-selling products, low-stock alerts, and monthly sales trends.

Retail Bike Store Sales Analysis using SQL: built a relational database, cleaned data (nulls, duplicates), and created advanced queries to analyze revenue, sales trends, top products, and customer insights. Enabled data-driven decisions and inventory optimization.

Jenson USA Sales & Operations Analysis is a SQL-based data analytics project aimed at deriving actionable business insights from transactional retail data. The project evaluates customer behaviour, staff performance, inventory efficiency, and store-level operations using structured queries.

I specialize in music store analysis using SQL, extracting insights from sales, inventory, and customer data. By optimizing queries and leveraging relational databases, I provide data-driven solutions to enhance business performance, identify trends, and improve decision-making in the music retail industry.