The ETL (Extract, Transform, Load) process is the foundation of data warehousing and enables organizations to integrate data from multiple operational systems into a centralized repository for analysis and decision-making. In a business environment, data is often distributed across e-commerce platforms, Enterprise Resource Planning (ERP) systems, and Customer Relationship Management (CRM) systems. These systems generate heterogeneous data in different formats, structures, and update frequencies. ETL consolidates this information into a unified data warehouse, ensuring consistency, accuracy, and reliability. The first stage is Extraction, where data is collected from various source systems without affecting their normal operations. In an e-commerce system, extracted data includes customer orders, product details, website transactions, payment records, shopping carts, and delivery information. ERP systems contribute financial transactions, inventory levels, procurement records, supplier information, production schedules, and employee data. CRM systems provide customer profiles, sales opportunities, service requests, marketing campaigns, and communication history. Extraction can be full or incremental. Full extraction retrieves all available data, while incremental extraction captures only newly added or modified records using timestamps, transaction logs, or change data capture techniques. The extracted data is temporarily stored in a staging area where further processing takes place. The second stage is Transformation, which converts raw data into a standardized and business-ready format. Since e-commerce,