The practice of web scraping has a poor reputation since it can be abused for unethical reasons. However, web scraping can also be put to beneficial use! In this article, we debunk some of the more widespread misunderstandings about web scraping so that you can gain a better understanding of the positive applications of this method.

1. Scraping is Only for Developers

This common myth must be debunked. Many workers without technological experience give up on managing their data before looking into it. Many scraping methods involve technical expertise, which developers have. New zero-code technologies are available. These technologies make pre-built data scrapers accessible to businesspeople, automating the scraping process. They include Facebook, Amazon, and Booking.com web scraping templates.

2. Scraping is Hacking

This is not the case at all. Hacking is a term that refers to a variety of criminal behaviors, the end consequence of which is often the exploitation of private computer networks or systems. Taking control of these allows one to engage in illegal acts such as stealing private information or manipulating systems for one’s own financial advantage. This is the purpose of gaining control of these.

On the other hand, web scraping refers to the process of obtaining information that is freely accessible from specific websites. Businesses often make use of this information in order to improve their ability to compete in their respective space. The end outcome for consumers is improved services and more equitable pricing in the market.

3. Scraping is simple

Many individuals hold the false belief that “scraping is a piece of cake.” They enquire, “What’s the issue? Just go to the website you’re targeting and collect the target information.” Conceptually, this makes sense, but in reality, scraping is a highly technical, labor-intensive, and resource-intensive process. Regardless of whether you decide to utilize Java, Selenium, PHP, or PhantomJs, you must continue to employ a technical team that is proficient in writing scripts in these languages.

Target websites frequently have intricate architectural designs and dynamic blocking systems. Data sets often need to be cleaned, synthesized, and structured after those challenges are surmounted in order for algorithms to evaluate them and derive useful insights. The fact is that scraping is really difficult.

4. For all target sites, just one scraper is required

Simply said, this is untrue. The first thing to remember is that there are many different website architectures. Consequently, if a company employs a scraper to collect feedback from Facebook users, it would require a different scraper for another platform, like Instagram. Even if you are using “Scraper A,” which was created exclusively for “Target site A,” you should keep in mind that websites frequently change their site architecture and add new blocking features. In order to adapt to changes that occur in real-time, it is, therefore, best to work with scrapers that have machine learning (ML) capabilities.

5. When data is acquired, it is “ready to use”

Usually, this is just not the case. When gathering target information, there are numerous factors to take into account. Consider the format that the data can be captured in as opposed to the format that your systems can ingest data in. Consider a scenario in which all the data you are gathering is in JSON format, but your systems can only handle CSV files. Prior to use, data must be structured, synthesized, and cleaned in addition to being in the proper format. For instance, this can involve deleting corrupted or duplicate files. The data cannot be evaluated or used until it has been formatted, cleansed, and organized.

6. Data scraping is a totally automated procedure

Many people think that information can be easily retrieved from websites by bots that merely crawl them at the touch of a button. This is untrue; the majority of web scraping is manual, and technical teams are needed to monitor the procedure and resolve problems. However, there are alternatives to automate this process that doesn’t entail getting involved in the intricate details of the data scraping procedure, such as employing a Data Collector tool or just purchasing pre-collected Datasets.

Frequently asked questions:

How accurate is web scraping?

It can quickly and affordably capture data from websites with a 90% accuracy rate. You are no longer forced to copy and paste endlessly into clumsy layout documents. But something might be forgotten. Behind online scraping, there are some restrictions and even dangers.

Can any website be scrapped?

You are free to scrape whatever website you like, as long as the data you collect is available to the public and you do not obtain information from private domains, which could contain confidential information.

Why do some websites not allow web scraping?

There are web scrapers available on the market that are free of charge and can scrape any website without causing any problems or getting blocked. There are a lot of websites on the internet that do not have any kind of anti-scraping system, but there are also websites that restrict scrapers because they do not believe in free data access.