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Web Scraping is the process of extracting large amounts of data from websites. The Web Scraper either saves them to their computer or transfers them to a spreadsheet. It automates the process of manually copying and pasting data that is made viewable through a web browser.

While Data Analysts have the ability to obtain increasingly rich data sources, they are limited by ways in which that data can be accessed and used. Web Scraping is important to learn so these Analysts can quickly and efficiently capture data from various sources in order to discover insights and make decisions.‎

Web Scraping services are in-demand thanks to the sophisticated technical skills required to get it done. Because organizations are seeing how effective data analysis can help their business grow, the demand for Web Scraping is expected to increase. Some industries that have the highest demand for Web Scraping include e-commerce, media, website creation, real estate, and others.

Some titles associated with Web Scraping include Data Scientist, Web Developer, Web Collection Specialist, Research Assistant, Application Developer, Web Mining Developer, Site Merchandiser, Market Intelligence Analyst, and of course, Web Scraper. In the U.S., Web Scraping can earn learners an average of $79,018 per year, according to ZipRecruiter.‎

Web Scraping courses offered through Coursera equip learners with knowledge in treating the internet as a source of data; working with HTML, XML, and JSON data formats in Python; using Python to access web data; getting and cleaning data; and more.

Lessons on Web Scraping are taught by instructors from major tech names and universities, including University of Michigan, John Hopkins University, and other organizations. Learners can enjoy exploring Web Scraping with instructors specializing in Programming, Biostatistics, Database Design, Web Development, and other disciplines. Course content on Web Scraping is delivered via video lectures, hands-on projects, readings, quizzes, and other types of assignments.‎

You'll need to understand and have experience using some programming languages before starting to learn web scraping. The most common language used in scraping is Python because it can handle all aspects of data extraction. Other languages you may need to be able to use before beginning your studies include Node.js, Ruby, C++, and PHP. You should also have experience using HTML and CSS.‎

If you're pursuing a career in Big Data analytics, machine learning, or artificial intelligence, learning web scraping is likely for you since these industries involve compiling large datasets, which web scraping is an integral part of. Industries that have the highest demand for people with web scraping skills are computer software, IT, and financial services, in particular jobs like data engineers, data scientists, and IT architects. If you are an analytical thinker, organized, and enjoy working with data, learning web scraping may be a good match for you.‎

People who are detail-oriented and enjoy focusing on the detail of work more than the big picture are well suited for roles in web scraping. Those who are innovative and look for unconventional, creative ways to accomplish a task also fit well into web scraping roles. Other people who are suited for roles in web scraping are those who enjoy data and technology, are adaptable and flexible, and aren't bothered by a high-pressure environment.‎

Topics related to web scraping that you can study include programming languages—especially Python—scripting, using Excel spreadsheets, and social media data analytics. You may enjoy studying research skills, the history of the internet, search engine optimization, search engine functions, and internet security topics.‎