Data scraping and collection involve the automated extraction of information from websites or digital sources. It's achieved using tools like Beautiful Soup and Requests in Python, which parse the HTML structure of web pages to gather desired data like text, images, and links. APIs can also be utilized for structured data extraction. However, challenges such as anti-scraping measures (CAPTCHA, IP blocking), website structural changes, and inconsistent data formatting can arise. To overcome these, techniques like rotating IP addresses, utilizing user-agent headers, and implementing retries can help mitigate anti-scraping mechanisms. Regular monitoring and updates to adapt to website changes are essential. Data validation and cleaning routines are crucial for maintaining data quality and uniformity.