How to Collect Public Data on the Internet
The internet allows us to connect people all around the world and share unimaginable amounts of knowledge and information. While new generations feel insensitive to the exponential development and growth of the digital world, it is arguably our most impressive creation. With the majority of the population incapable of living without an electronic device, we have never been more connected.
Depending on your perception of intelligence, an average human today can be smarter than our ancestors due to an enormous amount of data on the internet. The information accessibility has made the digital landscape the extension of our world for new options for communication, entertainment, trade, advertisement, and other niches susceptible to digitalization.
Ironically, with so much information available and its amount growing, data is the most valuable resource that empowers our advancements. Individuals, businesses, and large corporations utilize methods of information extraction to collect public data for personal projects, competitor analysis, marketing campaign improvements, and other tasks are driven by data.
While knowledge is power, such amounts of unorganized information do not give much value to a human brain to make appropriate decisions. However, the more data you have, the more precise decisions you can make, so how do you squeeze out this value?
The process of data extraction can be separated into two main components – data scraping and parsing. Businesses with technically proficient employees utilize them to get the most value from data aggregation.
So let’s talk about the basics of data collection. Web scraping defines the efficient use of automated bots to ensure continuous data extraction without interruptions. Once the extraction is successful, we end up with a line of code because the technology still has its means of communication. That is why we will also discuss data parsing. Because Python is a very common programming language for data extraction tasks, you also have to learn about parsing errors. Thankfully, Smartproxy is a legitimate proxy service provider that has blog posts to help you solve these issues and assist you to succeed in web scraping. Check them out to learn more about the service, its flexibility, and its applications.
How do you start web scraping?
Web scrapers are the tools that accelerate data collection. They allow you to lookup someone online in a company or business with his/her contact details. Even though every one of us can be perceived as a biological scraper, computers complete these tasks and store data with far greater efficiency. Because data aggregation is an inseparable part of the digital world, most students learn about web scraping in computer science programs in colleges and universities but there are many ways you can stumble upon the process of data extraction.
The best data scientist learns to scrape websites through trial and error. While the process gets more complex with bigger meaningful operations, a self-taught beginner can learn the basic Python coding knowledge to start using Scrapy and other frameworks to complete your first tasks. Wikipedia is a common practice target with tons of information for precise and calibrated extraction. Choose what data you want to extract and play around with until you see results for yourself!
Scrape with respect
Once you move to more complex and profitable scraping operations, you will see how protective some website owners can be about their public data. The goal of a successful web page or an online shop is to maximize real human traffic and eliminate bots that collect big amounts of information and stagnate their activity. Also, businesses keep changing their strategies based on web page analysis. If the page receives a lot of bot traffic, it can skew the data and make the information useless.
Web owners have different methods of stopping or minimizing bot traffic. Login requests, rate limiting, and other strategies can stop scrapers and DDoS in their tracks. However, because data is our primary priority, we can calibrate bots to treat others with respect. Do not bombard the server with data requests – find the best options to collect data with enough efficiency without taking advantage of others.
While businesses encounter competitors that guard their public data at all costs, you will still find companies that accept and depend on information extraction from others. Even more, some create application user interfaces (API) to give others access to data for easy distribution. If you want to respect website owners or even create lasting partnerships – contact them to get their opinion on the matter and use an API instead of slowing down web servers with unnecessary scraping. This way you get a straightforward approach to information without the need to worry about web scraping obstacles and parsing errors.
Learn about complementary tools
When you use a web scraper, data packets reach their destination with your IP address attached to them. Websites that want to prevent data extraction can blacklist your IP, or worse, redirect your connection to a decoy page to feed you false information – a honeypot.
To ensure the integrity of extracted data and protect your network identity, send your connection through intermediary servers. Residential proxies can protect your scraping bots with real IPs
from internet service providers, giving your data extraction operations a safety blanket. The best proxy service providers work with businesses to help them improve web scraping procedures.
Once you do not have to worry about the exposure of your IP address (this is a primary concern for most businesses), you can test your scraping bots and maximize their capabilities. With proxy servers and the knowledge accumulated along the way, you can collect public data without interruptions.
