Large Scale Data Extraction – 8 Web Scraping Challenges All Non-Techies Hate
Web scraping is becoming a blazing topic right among the people with the increased big data demand. An ever-increasing number of people are hungry for data extraction to support their market growth from different websites. Big data gives them the forefront in their sector, developments in the industry, consumer desires and competitive dynamics. Thus web scraping is far more than data gathering but a useful technique for businesses.
For example, you have developed a prototype of an incredible application that has achieved some excellent early traction. Data is the core of this application is the data scraped from a limited number of websites being scrapped (Let’s say 15). The app has proven to be quite useful, and it is now time to intensify data extraction by web scraping (Let’s say 1500 websites). However, the scale-up process becomes a very repetitive method, and the challenges that arise on a large-scale vary entirely from what you did in the early stages.
This is one of the biggest web scraping challenges that we from wscraper.com crush for many businesses. Whenever it comes to large-scale data extraction using web scraping, various roadblocks can emerge, restricting the next level growth of a dynamic application or enterprise. Although businesses may collect small data, difficulties occur as they switch to large-scale data extraction. This involves fighting the blocking mechanisms that stopped bots from large-scale web scraping.
What is the most frequent web crawling challenges that are faced during large-scale data extraction?
I have learned from critical discussions with some of my clients who, before hiring me, tried their web scraping projects themselves with generic scraping tools available out there just turned into a total mess. The main problems they have faced while running their web scraping projects are:
- Data hosting
- Detected by the target website and barred
- Complicated and evolving web architectures
- Geo-restrictions / IP blocking Technologies to prevent scraping
- The honeypot traps
- Data scraping in real-time
- Data accuracy
- Dynamic content
While we can overcome some of these challenges, you have to embrace others and proceed with the work. Let’s take a closer look at the large-scale web scraping challenges.
1. Data hosting
Large-scale data extraction produces a vast amount of information. If the data hosting framework is not adequately designed, search, filter and export of these data would become a time-consuming and cumbersome process. Therefore, the data warehousing or hosting system must be flexible, flawlessly fault-tolerant and safe for large-scale data extraction.
2. Detected by the target website and barred
Detected by the targeted website is quite a common problem since it is not challenging to track non-human behaviors online with today’s technology. When you scrap, you repeatedly send tons of queries, and, indeed, an average man couldn’t manage this, so web crawling/web scraping software is involved. To prevent this, you need many IPs that jump about and replicate human behavior to hide your scraping tool.
3. Complicated and evolving web architectures
The majority of web sites are built on HTML. Website designers may use their own parameters for designing the websites so that the website’s frameworks are very different. In such cases, You have to build an individual scraper for every website if you want to scrape several websites.
Each website updates its UI regularly to improve the digital experience and enhance its user experiences. This also results in many technical improvements to the website. As web crawlers are arranged to its code elements present on the website, the scrapers will also need adjustment. Web scrapers usually need to adjust every week since a small change in the targeted website impacting the fields you are scraping, depending on your built-in logic, may send you incorrect data or crash. The very last element you need to pump into your automated system is the bad training data.
To represent human actions, at wscraper.com, we use customizable workflows to interact with multiple pages. We create a custom algorithm to adapt to the workflow to the latest pages quickly.
4. Geo-restrictions / IP blocking Technologies to prevent scraping
Some websites deliberately utilize robust anti-scraping mechanisms that prevent crawling. LinkedIn is an ideal example of this. These websites use complex coding algorithms to avoid bot entry and enforce IP blocking protocols, even though one complies with legitimate and best web scraping practices.
In this context, geo-restrictions or IP blocking are a very common problem. IP blocking is a popular form of stopping web scrapers from manipulating web data. It usually arises anytime a site detects a large number of requests that have been made from one IP address. The website will either ban the IP entirely or block its access to crumble the scraping mechanism.
During a web scraping project, you want to gather the maximum amount of data from a website, but those data are not accessible in your country/region. Which means you miss many valuable details that might be of great value to you.
It requires a great deal of time, effort and money to create a technological approach to tackle the anti-scraping mechanisms.
5. The honeypot traps
Honeypot is a trick that the website’s creator places on the web pages to catch the scrapers. Many website designers include honeypot traps inside their website to trace web spiders. These sorts of pitfalls are links that are invisible to humans but noticeable to scrapers. Some of the honeypot links for detecting crawling would have the “display: none” CSS style or a masked color to match the page’s background color. When a scraper enters into the trap of a website, it can use the details it collects (its IP address) to block the scraper.
We are experts in using XPath to find identical objects to click or scrape, which significantly reduces the possibility of getting caught by the honeypot trap.
6. Data scraping in real-time
Data scraping in real-time is important when the matter comes to comparing prices and monitoring inventory. The data will shift at a glance, which can contribute to tremendous business profits for a company. The scraper must still track the websites around the clock and scrape the data. After all, it always requires some time for the request and data supply. Moreover, the acquisition of a large scale data in real-time is indeed a big challenge.
Our mastery in using timely programmed cloud extraction scrapes the target websites at an unsuspicious time interval to perform almost real-time scrapping.
7. Data accuracy
Data that do not conform with the consistency standards may impact overall data integrity. It is not easy to ensure that the data follow consistent instructions when crawling since it has to be done in real-time. Inaccurate data can trigger serious problems when you use up-to-date AI or ML technologies.
8. Dynamic content
Many websites use AJAX for updating its dynamic content. For example, prolonged image loading shows more info by clicking on a button by AJAX calls. On websites with such features, it is intuitive for the users to access and view any data, but it is rigorously strict for generic web scrapers.
We continuously develop solutions that can quickly scrape websites with numerous functions such as AJAX Load or scroll down the page.
Concluding
While particular challenges rely on the web scraping/web crawling method’s consistency and technical skill, many businesses today depend on the data, and you can not ignore it. Therefore, it is essential to choose experienced web scraping professionals that can quickly develop and include several functionalities that can be used for your own advantage and be specific about which details you want to crawl and where it can be found.
Web scraping would probably pose further challenges in the coming days, but there is still the same basic standard for scraping: handle the websites neatly. Do not overload it. Do not overcrowd it. Also, a professional web scraping like ours always handy to help you tackle your web scraping tasks.
