How to extract data from a website

Online price monitoring: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> to dynamically change pricing and stay competitive.
Real estate: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> data for building real-estate listings.
News aggregation: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> as an alternative data for finance/hedge funds.
Social media: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> scraping to get insights and metrics for social media strategy.
Review aggregation: <em style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\">scraping gathers reviews from predefined brand and reputation management sources.
Lead generation: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> the list of target websites is scraped to collect contact information.
Search engine results: <span style=\"font-size: 18px; color: rgb(0, 0, 0); background-color: transparent;\"> to support SEO strategy and monitor SERP.

Manually extracting data from a website (copy/pasting information to a spreadsheet) is time-consuming and difficult when dealing with big data. If the company has in-house developers, it is possible to build a web scraping pipeline. There are several ways of manual web scraping.

1. Code a web scraper with Python

It is possible to quickly build software with any general-purpose programming language like Java, JavaScript, PHP, C, C#, and so on. Nevertheless, Python is the top choice because of its simplicity and availability of libraries for developing a web scraper.

2. Use a data service

Data service is a professional web service providing research and data extraction according to business requirements. Similar services may be a good option if there is a budget for data extraction.

3. Use Excel for data extraction

This method may surprise you, but Microsoft Excel software can be a useful tool for data manipulation. With web scraping, you can easily get information saved in an excel sheet. The only problem is that this method can be used for extracting tables only.

4. Web scraping tools

Modern data extraction tools are the top robust no-code/low code solutions to support business processes. With three types of data extraction tools – batch processing, open-source, and cloud-based tools – you can create a cycle of web scraping and data analysis. So, let's review the best tools available on the market.