Web Data Scraping
Web data scraping refers to the methodologies, and tools for programmatically extracting structured data from websites, such as DOM parsing, API interaction, and headless browser automation.
6 Web Scraping Challenges & Practical Solutions
Web scraping, the process of extracting required data from web sources, is an essential tool; however, it is a technique fraught with challenges. See below the most common web scraping challenges and practical solutions to address them.
How to Implement Proxy Scraping Services
Websites track the IP address of every incoming request, and a high volume of traffic from a single IP is the signal of an automated bot. The solution is a proxy. A proxy server is an intermediary that stands between your scraper and the target website, forwarding your requests while masking your real IP address.
10 Web Scraping Techniques & Tools (From No-Code to AI)
Web scraping is not the only method for collecting data from websites. Various other methods (e.g., LLMs) are available, and each technique has trade-offs. See the best web scraping techniques, the benefits and limitations of each method, and practical tips on choosing the right approach for your data collection project: The “build vs.
Web Scraping Using Google Sheets (With Real Example)
Web scraping with Google Sheets does not require coding knowledge for basic use cases. Instead of writing code, you use formulas to automate the data extraction process, which are similar to Excel functions. Learn how to use all five built-in Google Sheets import functions: IMPORTHTML, IMPORTXML, IMPORTDATA, and IMPORTFEED with real-world examples.
7 Web Scraping Best Practices You Must Be Aware of
Many websites actively try to prevent or limit web scraping to protect their data. When planning a web scraping project, it’s important to balance technical, financial, and legal factors. See the top web scraping best practices for an ethical and successful web scraping: 1.
Scraping Financial Data Without Coding
While official financial data providers do offer APIs, these are often limited in scope, access, or flexibility especially for real-time or niche data needs. As a result, financial data scraping has become a common approach to collecting such information, typically using technologies like web scrapers, headless browsers, and HTML parsers.
Web Scraping vs Data Mining: Why the Confusion?
Web scraping and data mining are sometimes confused with each other because they are both linked to extracting value from something that is valuable only when processed. However, the definitions are quite different, and not understanding the difference can cause not realizing how these processes can create value for businesses.
ChatGPT Web Scraping: Tutorial & Applications
ChatGPT is an easy way to bring AI to web scraping, saving developers from manual parsing work that requires constant updates. Using LLMs is becoming one of the best web scraping practices.
Scraping Google Trends for Real-Time Insights
Google Trends is an excellent tool for businesses and content creators who want to stay ahead of customer behavior, spot emerging trends, and make data-driven decisions. This guide explains what Google Trends data is, the legality of scraping Google Trends, and use cases for leveraging Google Trends data.
Top 18 Web Scraping Applications & Use Cases
We have explained what a web crawler is and why web scraping is crucial for companies that rely on data-driven decision-making. Web scraping is important because regardless of industry, the web contains information that can provide actionable insights for businesses to gain an advantage over competitors.