5 Challenges With Data Extraction When Drilling Websites

Information is a key to explore innovative ways for simplifying a variety of business activities. Its source is data from Internet of Things (IoT), websites and news agencies. A fact that a 10% increase in their accessibility will up additional net income by more than $65 million for typical Fortune 1000 companies is worth noticing. It is also predicted that more than 50 billion smart connected devices will be here with us by 2020, which means that we are going to have more sources for data mining. It also signifies that the workload of a data extraction company is going to be more and more over time.

Data Extraction

Data scientists and researchers are looking forward to know more of target audience behavior and its psychology to understand how it can be converted into buyers. This whole process begins with web scraping, which is executed with a piece of code corresponding to the requests being sent for meeting a particular requirement. Then, parsing occurs in its HTML code, extracting what is targeted for.

5 Common Challenges in Web Scraping

But, this is not as easy as it sounds. There are many challenges that interfere with data extraction when you are going to drill websites.

1. No Standard Web Design Leads to Changing Codes

The drilling begins upon figuring out the structure of ecommerce sites. Simply put, you have to thoroughly observe the web architecture that you are going to drill in. The coder or programmer can set codes accordingly. But, this is a big concern because there is no standard layout of design of any eCommerce or other websites. Irrespective of intentional or amateur coding style, you have to navigate with bots over and over differently. Such doing requires time, effort and much of brainstorming, which is a big challenge.

2. Complex Site Elements Disturb Scraping

Like any other trend, web elements and characteristics are going to the next level to improve its responsiveness. This is all done to make customer’s web journey ultra smooth and fruitful. On the flip side, drawing details through scraper or codes has become way more difficult because of those extraordinary complex elements.

Simply put, the dynamic content in the websites puts many roadblocks, hampering the speed of loading images or capturing more information. The scrolling to trace that info continues to take place for a long time, making it hard to read data for scraping.

3. Anti-Scraping Protocols & Techs To Block

As a web owner, it’s good to have security protocols and techniques to hamper scraping attempts. For a data extraction company, it’s like a tug-of-war, wherein codes to deny copying content, JavaScript for rendering and user- agent validations are deployed to stop scraping.

Besides, there are some websites that put IP- constraints in place to monitor all requests. These protocols flag repeated requests in a short time from the same IP address as dubious or doubtful. This might ban further requests from sending. However, VPN can be changed, but some websites easily detect the masked IPaddresses, which halt your goals for a while.

4. An Old HoneyPot Trap Method Is Gold

This method is typically used for fooling hackers, which pushes them to interact with the IT trap at first. This is mostly done in the case of sites that carry useful intelligence at the backend. These kinds of traps have a capacity to detect crawlers using links strategically, which scrapers can hardly see on a webpage.

As the links detect any attempt from bots or anyone, they block all ways to crawl into further. As your codes set out the trigger, this trap goes active and instantly blocks the proceeding.

5. Captcha To Block Automated Scripts

Also called Completely Automated Public Turing Test to Tell Computers and Humans Apart, the Captcha is a significant Turing Test. This is basically harnessed to review if a machine is capable of automating as naturally as a human does.

It fortifies the web content, blocking automated scripts from capturing data over and over coming from the same site. So, captcha is integrated to let the bot solve it first and then, extract what it looks for. But, this is something that a robot cannot do it correctly.