As the race for real-time data access intensifies, organizations are confronting a growing legal and operational challenge: web scraping. What began as a fringe tactic by hobbyists has evolved into a sophisticated, multibillion-dollar ecosystem driven by commercial data aggregators.
Implementing a solution to identify and manage automated traffic can help organizations more effectively address the problem of web scraping and the countless other challenges associated with bad bots.
Alibaba's web scraping data leak exposed over 1 billion user records leading to the imprisonment of the implicated software developer and his employer for three years.
Web scraping can become a cautionary tale if it doesn’t comply with the GDPR, or, most recently, with the CCPA. What are the considerations and how can you do it successfully and with ease?
Companies who conduct web scraping or do business with data harvesters need to understand the nuanced legality of web scraping so they can better navigate the risks associated with the practice and protect themselves from liability.
France’s data protection watchdog CNIL has published a set of guidelines to provide GDPR guidance on web scraping for direct marketing and recommended actions to businesses.
LinkedIn has taken actions to terminate accounts suspected of web scraping however data analytics firm HiQ said the data was fair game for scraping. Where does the line between public and private data lies?







