Web Scraping

Web Scraping is also known as Screen Scraping, Web Data Extraction, Web Harvesting etc. It is a technique utilized to extract large amounts of data from various web sources (websites, FTP, APIs), in a quick, efficient & automated manner - saving data in more structured and usable format.

Web Scraping is a technology solution, which closely emulates and automates the human web surfing and steps involved in data extraction from different websites. In Web Scraping, before writing the web scraper, we know the target website and the exact navigation steps to reach the target web-page from which we need to scrap the data. We know the text pattern and HTML element structure of the web-page as they are fixed.

In an era of Data Science & Big Data, we need data from various online resources. Data can be grabbed from any FTP resource, from any website or using any API. Sometimes, data extraction processes involve many steps to reach out to the destination from where you can fetch the required data.

To give you more insight, in many organizations, the data analysis team hires people to extract data from various websites. Extracted data is then used by the Data Analysis team for further processing. Later, they apply data science techniques on this processed data.

For example, an organization wants reports on product/service reviews, feedback, complaints, brand monitoring, brand analysis, competitor analysis, overall sentiment towards the brand. To achieve this goal, first we need to collect data from various sources, like E-commerce websites and social media. Second, the data analysis operation is needed to be performed on provided datasets. The person in charge of data extraction collects all relevant data from social media websites, E-commerce websites and other websites. Then, te data analysis team uses this data for further processing and analysis to generate final reports. The whole data extraction process can be automated using Web Scraping.

Main component of web scraping:

  • Downloading Web Page or Data Source.
  • Extraction of data.
  • Saving data.

High-level workflow:

Use cases where we use web scraping:

  • Automobile Scraping: Data is scraped from automobile websites including classified sites, auto spare parts sites, etc. Data points can be product id, post title, location, seller details, make and model, description and prices.
  • Classified Listings: Scraping of unique content from classified listings like property listings.
  • Social Media Scraping: Companies are very interested in such data, which includes: brand monitoring, overall sentiment towards the brand, brand analysis, product/service reviews, feedback, complaints, competitor analysis, and so on.
  • E-commerce Scraping: Price & Product Review of e-commerce products can be scraped and used for competitor analysis. Many companies use it, so that they can keep an eye on their competitors.

For any of our case studies, feel free to reach out to us at IP@ondemandagility.com

-Abhishek Kumar Singh, Project Lead

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