Website scraping, which is also known as web scraping, data crawling, data scraping, web harvesting, and other similar names, is a way to collect data from websites.
Analysis of Website data inside the browser does not happen easily. Analysis often requires the collection and organization of web information into suitable formats and tools. One way to collect the data uses copy-and-paste of the information by hand into a spreadsheet, database, or other similar file. The process is tedious and can take tremendous amounts of labor and time.
Software can be written that automates this same process of collecting publicly available data. The software visits the pages that contain the information to be collected and then automatically copies and pastes the data into whatever file format is needed.
A big challenge is that the skills required to code or script scraping programs require very broad and deep experience. Software must be tailored to the specifics of each website as well as to the specific information sought. The learning curve to develop these skills is extremely steep.
Another challenge is that information is often not standardized. For example, phone numbers on one page can appear in many forms including with dashes, without dashes, with and without parenthesis, with and without spacing, 7 digits, 10 digits, etc. A human easily differentiates between each of these formats but software needs a very robust design to understand formating differences.
KDnuggets, the online platform that covers business analytics, big data, data mining, and data science, reports that the top 10 industries with the highest demand for web scraping are:
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