Types of APIs
Web Scraping API
The Functionality of Web Scraping
Data analytics has become a huge part of how organizations are run. Rightly so, because data is growing exponentially with the world going digital and with a high surge in data consumption across the world. Web scraping is by far the most sophisticated way to get structured data. Either you can be familiar with big data analytics or work with one of the best web scraping providers like PromptCloud.
There are all kinds of data on the internet like images, product info, and customer reviews from Yelp or Tripadvisor; that can be used for market research. You might be interested to know Google regularly uses data analytics to index its content and for marketing purposes. Web scraping runs on three core principles. First, it makes an HTTP request to the server, extracts data by parsing the code, and it saves the relevant data on the cloud or locally.
The Role of an Analyst in Web Scraping
Now, we understand what web scraping does, but how does it function? How exactly does an analyst help to put things in perspective and give direction for bots to do their thing? An analyst provides the URLs for scraping by shortlisting the websites first. Then pushes a code to the scraper that identifies elements to be scraped on the front end. An analyst can also identify the source of data located in the backend of the website by using relevant nest tags. Once the nest tags are identified, with the help of Python libraries, the analyst specifies the data types like title or rating, to parse and save. A data analyst also keeps a check on if the target data is refined or not, if the terms of services are met, if the data protection protocols have been followed, or if the website is at risk of crashing. An analyst is always mindful of these considerations, and hence web scraping is easily one of the best ways to get structured data.