Understanding Data Scraping
In computer science, data scraping, or web scraping, refers to extracting data from websites and saving it in local databases or other applications using computer software.
Data scraping finds numerous applications, such as collecting content, pricing information, or contact details from online sources.
Data scraping consists of two primary components
- Web crawler, often referred to as a “spider,” is an artificial intelligence mechanism that utilizes hyperlinks and search engines to scan and search for data on the internet, mimicking human behavior. When relevant data is discovered, it is sent to the web scraper.
- Web scraper is a specialized tool that extracts data from online web pages. It uses data beacons, such as XPath, CSS selectors, regex, or a combination of these protocols, to identify the desired data within the HTML file.
Leveraging Web Scraping
In market research, web scraping plays a significant role as it enables the pricing, monitoring, analysis, and collection of product/service data, which aids decision-making, content production, and marketing activities.
Automating Data Scraping for Efficiency and Precision
While manual data scraping is possible, automated methods are generally preferred due to their cost-effectiveness and speed.
However, web scraping is not always a straightforward process.
Since websites come in various formats, it is essential to ensure that your web scraper can handle the target sites’ specific requirements.
Leveraging Web Scraping for E-commerce
Web scraping is commonly used in e-commerce and sales to track prices and generate leads.
Additionally, investors are increasingly utilizing this technology for online financial transactions.
It automates data extraction from various sources and organizes the information in a structured manner for systematic analysis.