The 4 Challenges of Data Scraping and How to Overcome Them

Do you want to scrape content from a website but are unsure how to go about it? Data scraping, which used to be relatively straightforward to accomplish, has become increasingly challenging and difficult to scale.
5 min read
The 4 Challenges of Data Scraping and How To Overcome Them

You will learn about the pros and cons of the different routes in this article and how to gather data the fastest and most efficiently. 

Extracting data from a website presents four main challenges:

Challenge No. 1: Software 

Should you use a third-party vendor or build your own software infrastructure? 

Do-it-Yourself (DIY)

To create a data scraper, you can hire software developers to write proprietary code. There are multiple open-source Python packages available, for example: 

  • BeautifulSoup
  • Scrapy
  • Selenium

The benefit of proprietary coding is that the software is tailored to your current needs. However, the cost is high:

  • Hundreds of hours of coding
  • Software and hardware purchases and licenses
  • The proxy infrastructure and bandwidth will still cost you, and you will still have to pay even if the collection fails.

Software maintenance is one of the biggest challenges. When the target website changes its page structure, which happens very frequently, the crawler breaks, and the code needs to be repaired. 

And you’ll still need to overcome the other three challenges listed below. 

Data Scraping Tools

You may also use a third-party vendor such as Bright Data, specializing in this area.

Other software available on the internet may be old and outdated. Caveat emptor – buyer beware. If the website looks like it was created in the previous century, that may reflect on their software.   

Bright Data has a no-code platform called Web Scraper API that does all the data extraction, and you only pay for success. See below for more information.

Challenge No. 2: Blocking

Isn’t it frustrating trying to access a website only to be challenged with a puzzle to prove we are not robots? The irony is that the puzzle challenge is a robot!

Getting past the bots is not just a problem when accessing a website. To extract data from public websites, you’ll have to get past the robots standing guard at the gates. CAPTCHAs and ‘site sentries’ attempt to prevent bulk data collection. It’s a game of cat and mouse where the technical difficulty increases with time. Stepping carefully and successfully through the minefield is Bright Data’s superpower.  

Challenge No. 3: Speed & Scale

Both speed and scale of data scraping are related challenges that are influenced by the underlying proxy infrastructure: 

  • Many data scraping projects begin with tens of thousands of pages but quickly scale to millions 
  • Most data scraping tools have slow collection speeds and limited simultaneous requests per second. Make sure you check the vendor’s collection speed, factor in the number of pages needed, and consider the collection frequency. If you only need to scrape a small number of pages and you can schedule the collection to run at night, then this may not be an issue for you.  

Challenge No. 4: Data Accuracy 

Our previous discussion addressed why some software solutions may not be able to retrieve data at all or with partial success. Changes to the site’s page structure may break the crawler/data collector, causing the data to be incomplete or inaccurate. 

In addition to the accuracy and completeness of the dataset, check how the data will be delivered and in what format. The data must be integrated seamlessly into your existing systems. By tailoring your database schema, you can expedite the ETL process.  

Bright Data’s Solution

Bright Data’s newly developed platform, Web Scraper API, addresses these challenges.

It is a no-code, all-in-one solution that combines:

  • Bright Data’s residential proxy network and session management capabilities
  • Proprietary website unlocking technology
  • Advanced data collection and restructuring

The structured data is provided in CSV, Microsoft Excel, or JSON format, can be sent via email, webhook, API, or SFTP, and stored on any cloud storage platform. 

Who needs web data?

Who doesn’t? Below are just a few examples:

  • With Web Scraper API, eCommerce companies can compare their products and prices with those of their competitors, such as Amazon, Walmart, Target, Flipkart, and AliExpress.
  • Business owners are scraping social media sites such as TikTok, YouTube, and LinkedIn for lead enrichment or to find top influencers.
  • Real-estate companies compile a database of listings in their target markets.

Putting it all together

If you want to extract web data, you’ll want to consider:

  • Development/maintenance of your own solution versus using a third-party solution
  • What kind of proxy network does the company offer? Are they reliant on third-party vendors such as Bright Data for their infrastructure? How reliable is their network?
  • The software’s ability to overcome site obstacles and retrieve the required web data. What success rate can you expect? Does the bandwidth charge depend on whether a collection is successful or not? 
  • Does the company comply with data privacy laws? 

Additionally, consider whether you want a solution that includes:

  • Best-of-breed proxy network access
  • Maintenance of your web crawlers/data collectors
  • An account manager to take care of your day-to-day operations and business needs
  • 24×7 technical support