Web Scraping: Real-World Data Extraction Across Industries

Sukhmandeep Singh

šŸ“ Summary:

This project showcases my expertise in building robust web scraping pipelines tailored to different industries. Using tools like BeautifulSoup, Selenium, and requests, I extracted structured data from real-world websites for market analysis, lead generation, customer insight, and academic research.

šŸ” Methodology:

Tools: Python, BeautifulSoup, Selenium, requests, pandas, re
Techniques: DOM parsing, dynamic content handling, pagination, anti-bot countermeasures
Output Formats: CSV, JSON
Challenges Solved: CAPTCHA handling, user-agent rotation, inconsistent HTML structures

🧩 Included Projects:

✈ British Airways Review Scraper (Skytrax)
Extracted user reviews, ratings, and travel classes.
Applied sentiment analysis-ready formatting.
Used for evaluating passenger satisfaction and service trends.
šŸŽ“ Talentedge Course Catalog Scraper
Scraped course titles, descriptions, durations, fees, and instructors.
Enabled course comparison for career planning or partnership evaluation.
šŸ“ Google My Business Profile Scraper (GMB)
Collected business names, categories, ratings, addresses from Google Maps results.
Built for local SEO and B2B outreach automation.
Used Selenium with geolocation & scrolling logic.
šŸš— Cars24 Used Car Scraper
Scraped vehicle models, pricing, mileage, registration year, and locations.
Enabled dataset generation for a car price prediction project.

šŸ“ˆ Outcome:

Each scraper was designed for scalability and ease of re-use. These scripts supported real-world decision-making in education, travel, local marketing, and e-commerce. Demonstrated my ability to build modular, ethical, and accurate data collection solutions for both research and business use cases.
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Posted Sep 4, 2024

Each scraper was designed for scalability, ease of re-use and supported real-world decision-making in education, travel, local marketing, and e-commerce.

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British Airways Customer Reviews Analysis

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