The internet has plenty of data and it is easy to find any information on the web. You can copy and paste it to any source and use it for further analysis. But when it comes to finding a large dataset from the internet, the task of manually copying and pasting would be tedious.
You need huge amounts of data when you need to train your machine learning algorithm. Businesses also need this type of huge data to analyze and use in their market intelligence tools.
That’s when you need web scraping technology. Instead of manually getting the data, web scraping uses an intelligent and automated algorithm that obtains large data sets efficiently and quickly.
In this article, you will learn what web scraping is, how it works, its uses, and the best tools in the market for web scraping.
Web scraping, also known as data scraping, web harvesting, or data web extraction, is the process of gathering data from websites. It is a form of copying specific data from the web and copying it into a local database or spreadsheet for later analysis.
Web scraping is an automated method to obtain a significant amount of data from websites. The data you collect is unstructured data in HTML format and later converted to structured data in a spreadsheet or a database so that it can be used in various applications.
There are different methods to collect data through web-scraping algorithms. You can use online services, specific APIs, or even your own code to scrape data from scratch. Google, Twitter, Facebook, and more allow you to access their data in a structured format.
Web scraping requires two tools: Crawlers and scrapers. A crawler is an automated software that crawls the web to search for particular data following the links in your webpage while the scraper is a tool to extract data from the internet.
The main job of a web scraper is to extract all the data on a particular website. Ideally, it is best if you mention the type of data a user wants to extract. The web scraper will be able to scrape only that data faster.
The scraper obtains the required data from this HTML code and outputs this data in the format mentioned by the user and places the outputs in an Excel spreadsheet or a CSV file. The data can also be saved in JSON files.
The benefits of web scraping for businesses and individuals are endless. Each one has its own specific need for scraping data. The design of the scraper varies based on the complexity and the scope of the user’s needs.
Web scraping software scrapes business contact details like phone numbers and email addresses. They are scraped from yellow pages on the websites or from Google Maps business listings.
Thereby, you can get the email addresses and phone numbers to send bulk promotional and marketing emails which help to generate leads through email marketing.
When you analyze the scraped data, you will find the market prices of your competitor’s products and services and compare them with yours which helps you get a better picture of your business and do comprehensive research about your industry online.
This also helps you have constant monitoring of how your business fares among the customers and analyze your competitors’ activity online. This data will help you make better decisions for your business.
Businesses use web scraping to scrape the details of products from e-commerce websites and their competitors. You can extract details such as price, description, images, reviews, and ratings using web scraping software.
It allows the businesses to see how it impacts their pricing strategies and fix their optimal pricing for their products so they maximize their revenue.
A Web Scraper extracts data from different websites and uses it to analyze consumer trends. If you require specific data like the price of the latest electronic gadget, then the web scraper tool collects it from multiple websites.
Each website displays its information in a different format. Even within a single website, the information you are looking for might not be in the same format or spanned across multiple pages.
The web scraper helps you extract data from multiple websites and save it to a spreadsheet or database in a unified format. This makes it easy for you to analyze and visualize the data.
Machine Learning models require huge datasets to train them and the efficiency of the model depends on the quantity as well as the quantity of the training data set. Web scraping tools help you obtain voluminous data for training machine learning algorithms.
There are a variety of Web Scraping tools available. You must choose an ideal tool that matches your business requirements. To help you with that, this article covers the Five Best Web Scraping with their features.
ScraperAPI removes the difficulty of finding high-quality proxies and rotating proxy pools, which makes web scraping easier. It also detects bans, solves CAPTCHAs, and manages to geo-target.
ScraperAPI will return the HTML response from the target website when you send a request to the API interface or to the proxy port.
ParseHub’s API enables you to manage and run your projects and retrieve extracted data. The ParseHub API is designed around REST. It aims to have predictable URLs and uses HTTP verbs or methods like POST, GET, and PUT where possible.
ParseHub allows you to build web scrapers without writing a single line of code. Analysts, data scientists, and journalists use this tool to select the data they need.
You can store the scraped data on its cloud-based servers by either connecting to the REST API or downloading it as a CSV/Excel file.
You may find that ParseHub is scalable because it collects millions of data points which saves time copying and pasting data without writing code
This tool is also similar to ParseHub and caters to people who want to scrape data without writing code. This tool is easy for non-developers to work with because it has a friendly interface for the data extraction processes.
It provides cloud services to store and you can schedule a time for extraction. Octoparse makes use of the IP rotation feature to prevent IPs from getting blocked.
It allows scraping data from dynamic elements in the website such as dropdowns, log-in authentication, and AJAX, and you can download the results in CSV, Excel, or API formats.
Scrapy uses Python to build fast and scalable web crawling and web scraping frameworks. You may use this tool to crawl websites and extract structured data to use in data mining, information processing, automated testing, and historical archival.
Scrapy was originally built for web scraping but it is also used to extract data using its APIs. This framework handles all the functionalities that make building web crawlers difficult such as proxy middleware, querying requests, and more.
Diffbot offers APIs for AI-based extraction of web pages. It uses natural language processing to automatically categorize the scraped data into different types such as articles, products, discussions, and nav pages.
It automatically extracts the content into structured entities which can be downloaded as JSON. Diffbot has a feature called The Knowledge Graph that lets you search the huge database that it has built. It has entities such as people, products, articles, and discussions and tries to find the relationships between them.
Web scraping can be done by anyone and does not demand any expertise in coding. You can be a developer who wants to extract large data from numerous websites and use it in a different format to build solutions. Or you can be a marketer who wants to extract information to analyze data to scale your business.
But it is highly recommended to use proxies while scraping websites. Our premium proxies allow you to access geo-restricted content, bypass limits set by the target website, rotate IPs, and avoid browser footprints. This allows you to simulate human behavior and avoid anti-bot mechanisms set up by the target website.
Keep visiting our blogs to know more about web scraping and how to use it smartly.