Top 5 Challenges of Data Scraping and How to Overcome Them

thanks-web 21 Nov 2022

Earlier data scraping used to be easy – and surprisingly straightforward. Data scraping is not always a fun little game – especially when you face some web scraping challenges; you might as well call it rocket science. But there’s no problem without a solution or ways to overcome it.

Here are 5 challenges you might have come across during data scraping, but we are here to provide solutions.

1. Geo-Specific Scraping

Geo-specific scrapping is quite common. When a website blocks your accessibility based on your geographical location, you will fail to access the website and gather valuable information from it.

Solution

Use a data scrapper that comes with proxies for your country, so even when a website’s accessibility doesn’t identify your location, you can bypass that restriction.

2. Changes in web pages

Your data scraper may be the best and has been working all right for the past couple of months or even years, but when a website makes changes to its web pages, it will likely create challenges for you.

Solution

This problem doesn’t have a direct solution, but you can still work on your scrapper before you run data scrapping.

You Can Also Read: The Ultimate Guide to Review Scraping in 2023

3. Data Quality

Data scraping has one objective – to be able to use that data for your marketing or any such objective. And for that, you’ll need quality data. Sometimes, your scrapper will collect unorganized data, which can be deemed as poor quality.

Solution

Use a scrapper tool that extracts data in a structured format and downloads them for you in an understandable file.

4. Anti-bot measures

Some websites will specifically block bots or scrappers from prying on their website – and install a captcha to get rid of the same.

Solution

You can program your bot to slow down because it often a rate limit is used to perform bot blocking.

5. UI Interactions before scraping

You will find that many websites need to be scrolled to get more data, and scrappers are not programmed to scroll and gather data by default.

Solution

You can program your scrapper to automate the clicking and waiting process so that it will wait for the content to load. Although writing this code might not always be easy so you can find a scrapper that already has this feature implemented.

Conclusion

You will probably find challenges in programming your data scraper to overcome all these challenges as well. So, it is always a good decision to invest in good data scraping tools that have already been implemented with the solutions to all the major challenges.

 

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