Paper Title
Integration Automation in E-commerce Data Collection System

Abstract
The expansion of e-commerce has resulted in an extensive amount of consumer data, necessitating effective data collection and analysis to maintain competitiveness. However, data protection regulations and anti-scraping mechanisms create obstacles to automated data extraction. This paper introduces an automated approach utilizing web scraping to track Amazon product prices, availability, ratings, and reviews. The system integrates web scraping, cloud storage, and automatic alerts to enable real-time monitoring of online shopping. Consumers are able to track price changes, firms are able to observe market trends, and researchers are able to track consumers' behaviour. The paper also covers ethical considerations and technical matters to enable ethical data collection and compliance with anti-scraping laws. The findings summarize that data collection is able to enhance decision-making for online shopping. Keywords - E-commerce, Web Scraping, Amazon Price Tracking, Consumer Data, Data Collection, Data Analysis, Price Monitoring, Availability Tracking, Cloud Storage, Automated Alerts, Market Trends, Consumer Behaviour, Anti-Scraping Regulations, Ethical Data Collection, Real-time Monitoring, Decision-Making in E-commerce.