Automate Web Scraping with No Code – Extract Data From Web


  • No experience required


Web scraping also called web data extraction is an automated process of collecting publicly available information from a website. This is done with different tools that simulate the human behaviour of web surfing. The data gets exported into a standardized format that is more useful for the user such as a CSV, JSON,  Spreadsheet, or an API.

Web scraping could be useful for a large number of different industries, such as: Information Technology and Services, Financial Services, Marketing and Advertising, Insurance, Banking, Consulting, Online Media, etc.

It became an important process for businesses that make data-driven decisions. Some of the most common use cases of scraped data for businesses are:

  • Market research
  • Price monitoring
  • SEO monitoring
  • Machine Learning / AI
  • Content Marketing
  • Lead Generation
  • Competitive Analysis
  • Reviews scraping
  • Job board scraping
  • Social media monitoring
  • Teaching and research
  • many more…

As the Internet has grown enormously and more and more businesses rely on data extraction and web automation, the need for scraping tools is increasing.

Power Automate is a service that helps you create automated workflows between your favourite apps and services to synchronize files, get notifications, collect data, and more.

Desktop flows broaden the existing robotic process automation (RPA) capabilities in Power Automate and enable you to automate all repetitive desktop processes. It’s quicker and easier than ever to automate with the new intuitive Power Automate desktop flow designer using the prebuilt drag-and-drop actions or recording your own desktop flows to run later.

Leverage automation capabilities in Power Automate. Create flows, interact with everyday tools such as email and excel or work with modern and legacy applications.

We will use Power Automate Desktop to automate the scraping of web data.

Who this course is for:

  • Beginners to Web Scraping
  • Beginner Data Analyst
  • Beginner Data Scientist
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