Basics of Web Scraping for Entrepreneurs and Startups

Definitions of Web Scraping and Synonyms

Hi everyone, I’m Alex, cofounder at DataOx, an IT company with more than five years of experience in data scraping.

This article is written for startups and entrepreneurs, mostly nontechnical businesspeople who want to know more about how data scraping can benefit their businesses. In this article, I’ll  explain how data scraping works and the main points to pay attention to if you want to use these technologies to grow your business.

First of all, let’s understand the terms used to define data scraping. There are a variety of terms like web scraping, web crawling, data parsing, data aggregation, and so on. My goal is to help you understand the scraping “ecosystem,” so you will find a comprehensive glossary at the end of this article. I define and apply these terms as they are most commonly used in the data scraping market.

 

Web scraping schema image#1

Web data scraping is an automatic process of copying data from web sources and storing it in a database or other storage format (Excel, JSON, etc.).

Basically, web scraping software contains two parts: a web crawler and a data parser (See Image 1).

A web crawler (or web spider) is an automatic software that visits web pages and websites using specific links (or URL addresses) and downloads and stores all available HTML code. After all content is stored in the database, the data parser starts to comb through the “raw” data to structure it according to specific rules.

In addition to web scraping, a web source finder is a software that finds required websites or web pages through Google or another search engine and sends links to be crawled by the web spider.

This is the basic process of web scraping. Let’s look at the different types of tasks and projects.

 

Kinds of Data Scraping Projects

Kinds of data scraping image#2
Each project has a unique amount of work, and the project price is determined according to each part, which is illustrated in Image 1.

Some projects require more complex web crawling systems but pretty simple data parsing, and other projects need complex data extraction and parsing solutions and relatively simple crawling processes. Each website requires a custom web scraper depending on the website’s complexity.

Data can be scraped once or on a regular basis. The latter is called web monitoring. It allows you to track any changes on the websites of your choice. For example, you might want to monitor the price of goods or the number of subscribers on a competitor’s YouTube channel. These factors can increase and decrease, so web monitoring helps you stay on top of these changes.

Web scraping projects can be implemented in two ways: through data delivery or through custom web application development. With the first option, you get just scraped data, but with the second one, you buy custom web scraping software developed just for your purposes. (Read more about that on our services page).

 

Approaches to Web Data Scraping Projects

Do it yourself web data scraping image#3
Do it yourself

There are two basic approaches to data scraping: the enterprise approach and the individual approach (or DIY).

As an individual, the simple DIY approach involves the use of numerous off-the-shelf tools on the market. They are either free or are sold inexpensively as a subscription. Great examples are import.io and Octoparse, among others.

This approach is suitable for those who just need to scrape data from some uncomplicated and unprotected websites (for example, online news sources).

But with this approach, you have to understand the tool and configure it all yourself. And ready-made tools usually do not work very stably, but it depends on the site.

If you want to build your own product based on scraping technologies, then using ready-made tools is unlikely to suit you, as there are many instances where they may not work.
So let’s talk about the enterprise approach, how it works, and what difficulties you might encounter with it.

Enterprise approach to data scraping image#4
Enterprise approach to data scraping

The enterprise approach assumes that a custom-made web scraping software should be developed for your custom requirements. You can outsource this task to a specialized company like DataOx or hire in-house staff.
Another model is possible: data delivery. This is when you can simply order the data from a contractor company if your business model allows for it

 

Top Three Common Web Scraping Challenges

Proxy services issues image#5
Proxy services

A proxy server is a remote computer with its own IP address. As a rule, if you want to collect a lot of data or collect it regularly from one site, the site will block you sooner or later by IP address, and to get around this issue, you need to have hundreds or thousands of unique IP addresses.

To solve this issue, you can use proxy servers. There are dozens of proxy services that sell access to proxy servers, and each has its pros and cons. There are many approaches to using proxy servers, and I will not dwell on them here in detail. You can find more information about this in our blog.

Captcha protection image#6
Captcha protection

Captcha protection poses another barrier to data scraping. You have probably seen this security feature on some websites. Captcha is a special picture that humans can recognize to continue working with a web page, but data scraping software cannot. Some special services solve this by automatically sending the captcha to a human, who inputs the answer and returns it, preventing the website from kicking off the bot (i.e., the. web scraper).

Professionally protected sites image#7
Professionally protected sites

The biggest difficulty to data scraping is when the website is professionally protected with services such as Imperva Bot Management or Akamai. This problem can only be solved by companies professionally engaged in data scraping. A few examples of company sites secured like this are LinkedIn, Glassdoor, and even British Airways. This defense is very complex and multifactorial and uses artificial intelligence. For each such resource, you need to select your own set of tools and change them over time.

We helped a few clients whose web scraping projects stopped scraping data from particular sites after only a few months. So before you build a product based on data scraping, we highly recommend getting a professional consultation with DataOx. This problem can occur even in the later stages of data scraping development, so always consult a professional to help you collect data at the speed you need.

Professionally protected sites at at data-ox

What Is an API?

Application programming interfaces or APIs are special “gateways” through which the site itself provides data so that it won’t be scraped. APIs usually have limitations in the first place, and they cost money. Here you need to check immediately whether it is possible to use the site API. But even with an API, there is no guarantee that a website will not change its policy tomorrow.

 

What is Web Scraping Used for?

You might already know the area where you are going to implement a data scraping project, but DataOx provides examples of the projects and industries we’ve worked for on our services page.

News scraping and monitoringJob post scraping
Brand reputation monitoringReal estate market scraping
Lead generation (scraping business contacts)Data scraping for machine learning tasks
Price monitoring solutionsReview scraping
Website URL scrapingFlight data monitoring
Social media scraping Data scraping
for the eCommerce industry

 

and more!

To get more information about web scraping, crawling, and other data processing, schedule a short free consultation with our data expert!

Glossary

  • Data extraction is a very broad term that is the process of retrieving data from any source: websites, databases, or even physical sources like newspapers, books, and reports. Web data extraction then is a synonym for web scraping.
  • Web crawling (web spidering) is the data scraping technology that visits web pages and websites and copies all available HTML code, including web page content. This term comes from search engines. Their web scrapers regularly visit all websites and scrape the available content
  • Web data aggregation (or web data compiling) is the process of scraping data from different websites, matching it, and removing duplicate data as necessary.
  • Web data monitoring is the process of regular website scraping and analyzing changes over time.
  • Incremental web scraping is a kind of web data monitoring where the client collects only new data added to a particular web source. For example, only the most recent news articles will be scraped from a news platform.
  • Data parsing is the process of analysis and structuring unstructured (“raw”) text or pictures to get cleansed, standard, and workable data. Parsers are able to transform raw data into tables and structure it using any criteria.
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