Why Data Scraping is an Essential Tool for Business Success in the Digital Age

The expansion of the digital economy has raised data volumes to unprecedented heights. Businesses need data to make better-informed decisions, and data scraping has emerged as an essential tool to fetch information from websites and other sources. So, what is data scraping and why should you know about it? Data scraping allows businesses to gather data from various sources and create a centralized repository of data that can be easily mined for insights. Data scientists then use this data to analyze patterns, trends, correlations, outliers, and anomalies. All this date-based information gathering then helps businesses to make better-informed decisions. This beginner’s guide provides an all-encompassing introduction to data scraping, including what it is, its uses, and the steps involved in the process.

What is Data Scraping?

Simply put, data scraping is the process of extracting data from websites, databases, and other sources. Furthermore, this data extraction can be done manually or by using automated data scraping tools like web crawlers or data extractors.

The data thus extracted includes text, images, videos, etc. It enables businesses to get a better understanding of their market and customers and allows them to gain deeper insights into customer behavior and preferences. This data can then be used to make informed decisions about product offerings, marketing strategies, etc. Think about it like this: data scraping is like copying text from an online source into your word document, but on a larger scale.

Typically, when people talk about web scrapers, they are usually referring to computer applications. Web scraping software (often referred to as “bots”) has been specifically designed to visit websites, explore essential pages, and extract meaningful data.

Also Read: What is Big Data? A Complete Guide on its Advantages and its Uses

Information Extracted From Data Scraping

You can scrape the following data from the web:

• Customer sentiments and reviews (from sites like Twitter or Amazon)
• Images
• Text
• Pricing from comparison websites
• Videos
• Product information

What is a Web Scraper?

A web scraper is a data-extraction tool that automates the process of extracting information from websites and other sources. It is essentially a bot or computer program designed to go through web pages, extract data, and store it in an organized way.

All such tools follow three fundamental steps:

1. Make an HTTP request to a server
2. Extract and break down the website’s code
3. Save the relevant data locally

Step 1: Make an HTTP Request to a Server

The data scraper needs to make an HTTP request before it can start data extraction. An HTTP request is a data packet that contains the URL of the page, information about how the data should be rendered (HTML or XML), and other data about the session.

Once the server receives this information, it will respond with an HTML document containing all the data the web scraper needs.

Step 2: Extract and Break Down the Website’s Code

The next step for the data extractor is to analyze and parse the HTML document in order to find any relevant data from it. This could include text, videos, images, etc. The data extractor will then “scrape” these elements off the webpage and store them in a data structure like the JavaScript Object Notation, better known as JSON.

Step 3: Save the Relevant Data Locally

As a final step, the data extractor will save all collected and organized data to a local file on your computer for further analysis. To ensure you get the data you need, the bot is programmed to extract predefined information from its source. Typically, stored in a .csv or .xls file, the structured data is converted into an Excel document for easy organization and access.

What are the Use Cases of Data Scraping?

Businesses and data professionals use data scraping for a variety of purposes, including:

• Tracking competitor data, such as pricing, reviews, customer sentiment, and product data
• Researching industry trends and insights that would otherwise be difficult to find
• Facilitating data-driven marketing campaigns based on consumer preferences
• Monitoring brand presence online and identifying negative feedback or sentiments about the company’s products or services
• Automating data entry processes, saving both time and money for businesses of all sizes
• Analyzing data from social media platforms like Twitter and Instagram for user behavior analysis or opinion mining
• Analyzing the stock market, tracking stock prices, and studying market trends over time
• Storing large volumes of data in data warehouses
• Reviewing product pricing, reviews, availability, etc, for e-commerce purposes

The Best Data Scraping Tools

There are various data-scraping tools you can use,  each suited for a particular need. Some of the most popular ones used today include:

Scrapy

Scrapy is a powerful and efficient tool to extract data from the web. This Python-based application framework provides access to valuable information in an organized manner. You can use it for scraping websites, crawling sites, or fetching data through APIs. It has a vast range of applications, including mining, processing information, and archiving old content. This is why Scrapy is a must-have for anyone trying to optimize their workflows.

Octoparse

This easy-to-use data-scraping tool is for both data extraction and web automation tasks. Octoparse provides a visual drag-and-drop interface to quickly build data extraction workflows. The best part is that you can use it even if you don’t have any programming knowledge or experience.

ScraperAPI

With this cloud-based data-scraping service, you can easily extract data from hundreds of sources in just a few lines of code. ScraperAPI also offers advanced features like IP rotation and CAPTCHA-solving capabilities.

ParseHub

Parsehub is great for those who don’t have extensive coding experience. This free online tool makes scraping digital data extremely simple and straightforward. Of course, full functionality requires an upgrade to the paid version. However, even just using the basic features can be rewarding.

Webhose.io

This cloud-based data extraction service enables users to quickly scrape data from webpages, search engines, and social media platforms in real-time. Webhose also offers automated data cleansing capabilities for large data sets.

BeautifulSoup

For many data analysts, BeautifulSoup is the go-to tool for parsing XML and HTML documents. Its ability to turn vast amounts of information into organized tree structures takes away much of the hassle associated with navigating complex data sets. The tool works with the Python library, which means a quick and efficient analysis of large data volumes.

Develop Data Science Expertise with Emeritus

Data-scraping tools are your best bet to extract data efficiently. Whether you’re a data analyst or data scientist, data scraping can help you automate tedious processes and uncover valuable insights into customer behavior. And if you want to know everything there is to know about the topic, Emeritus’ data science courses are just the way to do it.