Anil Kumar Mohanlal

This project aims to develop an advanced UiPath-based automation solution designed to systematically extract and analyze property-related data from municipal websites across Israel. The automation tool focuses on retrieving detailed information about buildings and flats, including their ownership status, occupancy, and availability for rent or sale. This solution can efficiently handle and process complex Hebrew-language PDF documents by leveraging UiPath's powerful automation capabilities and ABBYY's OCR technology.

OBJECTIVES
• Data Extraction: Automatically collect comprehensive data from various Israeli municipal websites. This includes scraping property records, occupancy statuses, and details about flats and buildings.
• Data Processing: Utilize ABBYY OCR technology to extract and interpret Hebrew text from scanned PDF documents and images, ensuring accurate data extraction.
• Status Analysis: Categorize and analyze the extracted data to determine property statuses, such as whether a building is occupied, available for rent, or up for sale.
• Operational Efficiency: Implement a robust UiPath workflow that can run continuously for extended periods (up to 24 days) to ensure thorough and up-to-date data collection.

In the modern digital landscape, eCommerce platforms have become central to business operations and consumer experiences. As these platforms generate massive volumes of data, businesses and analysts increasingly seek to harness this information for competitive advantage. UiPath, a leading robotic process automation (RPA) tool, offers robust capabilities for automating data extraction processes, making it an invaluable asset for organizations aiming to glean insights from eCommerce websites. This article explores the intricacies of data extraction from eCommerce websites using UiPath, detailing the benefits, challenges, and implementation strategies involved.

UNDERSTANDING THE NEED FOR DATA EXTRACTION
eCommerce websites are rich sources of data, encompassing product information, pricing, customer reviews, inventory levels, and more. Extracting this data can provide valuable insights into market trends, consumer behavior, competitive positioning, and product performance. Key use cases for eCommerce data extraction include:

• Market research
• Price monitoring
• Product aggregation
• Sentiment analysis

Users email the list of container numbers to RPA email accounts which prompts the robot to reach this email, download the Excel attachment, and go to different shipper sites to search for container number, location, the estimated time of departure (ETD), and the estimated time of arrival (ETA). After the robot collects all this information, it emails back details to the sender.