SQL

 This SQL project analyzes sales data to extract insights for strategic decisions, covering metrics like total sales and profit, as well as trends in sales distribution. 

 This SQL-driven customer segmentation project explores diverse aspects of an e-commerce dataset, including demographics, purchasing behavior, and satisfaction levels. total customer count, popular categories. 

 This SQL project aims to detect fraud within transactional data by querying for anomalies or irregular patterns suggestive of fraudulent activity 

This SQL music store analysis project delves into customer behavior, sales patterns, and genre preferences. It identifies senior employees, top-selling countries, high-spending customers, and best-selling albums, aiding strategic decision-making. Advanced queries explore customer spending on artists, popular genres by country, and top-spending customers, providing valuable insights for marketing strategies.

 This SQL project examines India Census datasets to analyze population demographics, literacy rates, and growth trends by state. It computes metrics such as average growth, literacy rates, and sex ratios, aiding in understanding socio-economic patterns. Additionally, it identifies top-performing states and districts based on growth, literacy rates, and sex ratios.