This repository contains a full-scale SQL data analytics project designed to solve real-world business problems. Using a dataset focused on sales and customer behavior, the project progresses from basic data exploration to advanced analytical techniques like cumulative analysis, performance tracking, and customer segmentation.
- Changes Over Time Analysis: Tracking trends and seasonality in sales data.
- Cumulative Analysis: Implementing running totals and year-to-date (YTD) calculations.
- Performance Analysis: Comparing current metrics against historical benchmarks and targets.
- Part-to-Whole Analysis: Evaluating the contribution of specific categories or products to the total business.
- Data Segmentation: Categorizing customers and products into groups (e.g., high-value vs. low-value) for targeted strategy.
- Automated Reporting: Building dynamic SQL scripts to generate Customer and Product performance reports.
- Changes_Over_Time.sql: Analysis of sales evolution across different time periods.
- Cumulative_Analysis.sql: Logic for running totals and cumulative growth metrics.
- Performance_Analysis.sql: Code for identifying top/bottom performing entities.
- Data_Segmentation.sql: Scripts for customer and product tiering.
- Final_Reports.sql: Consolidated queries for stakeholder-ready reporting.
