Harnessing Public Web Data for AI

Organizations strive to acquire data through effective, reliable, and accessible means. As far back as 2006, British Mathematician Clive Humby likened data to the new oil, but in development, some argue that our time is the new oil.

This guide will cover the following:

• Methods of data acquisition
• Technical challenges and solutions in data collection
• Practical examples for developers to gather data

Utilizing publicly available web data in artificial intelligence (AI) using quality data aids the performance and applicability of AI models, making them intelligent and responsive to real-world scenarios by adequately training and enhancing the systems. Bright Data as a service can help to make this happen.

Let’s dive in.

Methods of data acquisition

Web scraping

Web scraping is all about extracting relevant or specific data from a website. The data can be converted and exported in a structured format like JSON, CSV, or Excel.

Gathering data involves various techniques, which are time-consuming and prone to errors when working with large datasets manually. Another way is using automated software tools or scripts such as HTML parsing, DOM manipulation, or API interaction, which can be tricky because if the structure of the web page syntax changes, like elements or class names, the converted data becomes useless.

From a developer's standpoint, how do you scrape public web data successfully? Bright Data offers proxy networks with its infrastructure that allows you to bypass location restrictions using a different configured and verified IP address without getting flagged by target websites. Other ways are known to help make scraping possible. Bright Data has a solution for all of them:

• Automate website unlocking management
• Interact with websites
• Build scrapers

In addition, Bright Data has pre-configured datasets available in the dataset marketplace. The advantages of using the marketplace to search for a dataset for your use case are that it is 100% compliant with the CCPA and GDPR standards, reliability, and time-saving capability. Therefore, it means there is security, and data is not leaked on your personal identifiable information (PII).

Using the web scraper APIs, you can programmatically access structured web data from dozens of popular domains, such as LinkedIn, Crunchbase, Amazon, Indeed, Glassdoor, and so on, whose data are available for $0.001/record cost.

Technical challenges and solutions in data collection

The challenges arise from unethical practices such as scraping web data without following the guidelines outlined by some target websites on what is permissible. Some specialized anti-bot technologies identify when you hit too many requests at any time, preventing you from accessing the website.

1. Managing proxies

   As discussed above, to avoid your internet protocol (IP) bans and rate limiting, you cannot write automated scripts to act like humans, which will block your IP once identified. The solution uses a proxy service to rotate IP addresses across different data centers with a powerful server to send requests.

   
   

   Bright Data rotating proxies are spread across 195 countries with a 99.99% delivery success rate.

   
   

2. Automation scripts

   Developers write scripts that can handle dynamic content on a website that is not static due to constant changes from management. While developers can write scripts in different programming languages, the question is, are you ready to modify the code every time a change occurs on a target website?

   
   

   With Bright Data, you can power up scraping data with a headless browser suitable to run your Puppeteer, Selenium, and Playwright with CAPTCHA auto-solver without lifting a finger on your behalf. How magical that is.

   
   

   Bright Data comes with pre-written scripts that you can adapt to your workflow as a developer.

Practical examples for developers to gather data

As a developer, check out this guide on extracting reviews in a JSON file using the Scraping Browser and ChatGPT to build a frontend application with the data gathered and captured.

For this application, we got the data from the Udemy website for a course on the platform and used ChatGPT appropriately.

Conclusion

In this article, you learned the usefulness of public web data and how to harness it for AI. The uniqueness of this is knowing how public web data serves as training datasets for models, which is effective for business owners or individuals for research purposes.

Bright Data is globally acclaimed as a top provider of proxy networks and AI-powered web scrapers trusted by tens of thousands of Fortune 500 companies and over 20,000 customers.

Finally, as shown by the data gathering example, Bright Data is compatible with many coding languages, tools, and BI software.

Try it today!

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