

Augustas Pelakauskas
Last updated on
2024-08-30
1 min read
AI Summary:
Web scraping is essential for data-driven businesses, but this method frequently encounters challenges, especially when collecting web data at scale. This post introduces a white paper detailing methods and solutions to minimize frequently occurring issues, enabling more reliable data extraction.
Web scraping is an essential practice for data-driven businesses. Acquiring and analyzing large amounts of public data can unveil surprising insights, creating new avenues for business growth.
The obstacle experienced by anyone who has ever tried web scraping is getting blocked. For many reasons, websites aren’t too keen on letting automated scripts browse their content freely. As a result, many web scraping newcomers get blacklisted and lose access to target content.
Even when collecting data with the best intentions, getting blocked is still possible. Websites have a hard time differentiating between good and bad bots and often enact blanket bans that stop most scripts from working.
Over the years spent in the web data industry, we have collected many insights that help avoid blocks. Following the steps outlined in this white paper, you can scrape freely and get banned less frequently.
Free PDF

In this whitepaper, you’ll find the following nuances of minimizing blocks when web scraping:
Things to know before scraping
Actions to implement when scraping
The complexities of anti-bot measures
Oxylabs solution for large-scale data extraction
Explore other web data collection topics detailed in Oxylabs’ white papers.


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