SQL Data Analysis

This project contains SQL scripts designed to perform data analysis on sales and customer datasets within a Data Warehouse structure.
The main goal is to generate reports and metrics that can be used in Business Intelligence (BI) scenarios.

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📂 Project Structure

sql_data_analysis/ ├── category_sales_contribution.sql # Category-wise total sales and percentage contribution ├── customer_metrics_report.sql # Customer metrics, age groups, and segmentation analysis ├── customer_segments_by_spending.sql # Customer segmentation based on spending behavior ├── monthly_running_sales.sql # Monthly and cumulative sales report ├── monthly_sales_report.sql # Monthly sales summary ├── product_price_segments.sql # Number of products by price range ├── yearly_product_performance.sql # Yearly performance analysis of products └── datasets/ # Datasets used in the analysis

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📊 Analysis & Reports

1. Sales Analysis

• Monthly total sales
• Cumulative sales trends
• Sales contribution by category
• Product distribution by price segments

2. Customer Analysis

• Customer distribution by age group
• VIP / Regular / New segmentation
• Average Order Value (AOV) and average monthly spend

3. Product Performance Analysis

• Year-over-year sales changes
• Above/Below average sales classification
• Annual performance comparisons

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📂 Dataset

• Folder: datasets/
• Example Data: Sales, customer, and product tables
• Schema:
  • fact_sales: order details (date, product, customer, sales amount)
  • dim_products: product details (category, price, name)
  • dim_customers: customer details (age, name, customer number)

Note: No real data is used; analyses are performed on sample or synthetic datasets.

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🚀 Usage

1. Open the .sql files in SQL Server Management Studio (SSMS) or a compatible SQL editor.
2. Run the queries on the respective database schema.
3. Use the results for reporting, data visualization, or Business Intelligence dashboards.