Businesses generate large volumes of sales data, but raw data alone does not provide actionable insights. This project focuses on analyzing sales data using SQL Server to uncover trends, identify top-performing segments, and support data-driven decision-making.
- Analyze overall sales and profit performance
- Identify top-performing products and categories
- Evaluate region-wise sales contribution
- Analyze monthly sales trends
- Generate key business KPIs using SQL
- Sales transaction dataset
- Features include Order ID, Product, Region, Sales, Profit, and Order Date
- Data stored in structured relational format
- SQL Server
- Excel / CSV
- SELECT, WHERE, GROUP BY
- ORDER BY
- Aggregate Functions (SUM, COUNT, AVG)
- JOIN operations
- Subqueries
- CASE statements
- Explored and cleaned sales data
- Wrote SQL queries to calculate key metrics
- Performed product, region, and time-based analysis
- Generated insights to support business decisions
- Identified highest revenue-generating region
- Determined top-performing products and categories
- Observed monthly sales trends and peak periods
- Analyzed customer contribution to total revenue
- Helps businesses focus on high-performing products
- Supports regional sales strategy optimization
- Improves decision-making using data-driven insights
- Enables tracking of key performance indicators
- SQL_Sales_Project.sql — SQL queries
- Sales Performance & Business Insights using SQL Server.pdf — project output
- README.md — project documentation
- Import dataset into SQL Server
- Open SQL_Sales_Project.sql
- Execute queries step-by-step
- Analyze output and compare with results
Sanman Kadam
MSc Statistics Student | Aspiring Data Analyst
GitHub: https://github.com/the-irritater