We live in an era when making data-driven business decisions is the number one priority for many companies. To fuel these decisions, companies track, monitor, and record relevant data 24/7. Fortunately, there is a lot of data stored on servers across websites.
It has become common for various companies to extract data for their businesses purposes. However, this is not one of those processes that you can implement in your day to day operations before getting informed. If you are just searching how to easily start web scraping, check out Oxylabs’ Real-Time Crawler that ensures 100% delivery from search engines and e-commerce websites.
If you feel that it is too early to think about web scraping tools for your business because you need more knowledge in this area, we have put together an article that will help you understand how to extract data from a website and what challenges await you as you go further up the data scraping path.
Why extract data from website in the first place
Big data is a new buzz word in the business world. It encompasses various processes done on data sets with a few goals – getting meaningful insights, identifying trends and patterns, and forecasting economic conditions. For example, web scraping real estate data helps to analyze essential influences in this industry. Also, web scraping can be useful in the automotive industry. Businesses collect such automotive industry data as users and auto parts reviews, and much more.
Various companies extract data from websites to make their data sets more relevant and up-to-date. This practice often extends to other websites as well, so that the data set can be complete. The more data, the better, as it provides more reference points and renders the entire data set more valid.
While these are strong reasons for extracting data from a website, there are a couple more. The process is entirely automatic and results in no errors. Instead of endlessly copy-pasting, your employees will be able to focus on more pressing matters.
Web scraping tools also streamline data management and aggregate data so that you can understand it easily.
How data extraction works
If you are a not-that-tech-savvy person, data extraction can seem like a very complicated and incomprehensible matter. Actually, it is not that complicated to comprehend the entire process.
The process of extracting data from websites is called web scraping. Sometimes you can find it referred to as web harvesting as well. The term typically refers to automated data extraction processes using a bot or web crawler. Also, you can find information where the concept of web scraping is confused with web crawling. If you want to find out the main differences between these terms, check out our other blog post: Web Scraping vs. Web Crawling.
We’ll go over step by step to fully understand how data extraction works.
What makes data extraction possible
We have HTML to thank for making extracting data from web pages possible. HTML is a text-based mark-up language. It defines the structure of the website’s content via various components, including tags such as “paragraph,” “table,” and “page title.”
Thanks to the structured nature of HTML web pages, developers are able to come up with scripts that go through them and pull data from specific HTML tags.
Building data extraction scripts
Everything starts with building data extraction scripts. Programmers skilled in certain programming languages such as Python can develop data extraction scripts, so-called scraper bots. Python advantages such as diverse libraries, simplicity, and active community make it the most popular programming language for writing web scraping scripts. These Python web scraping scripts are able to automate data extraction completely. They send a request to a server, hop onto a website, go through every previously defined page, HTML tag, and components. Then they pull data from them.
Developing various data crawling patterns
Data extraction scripts can be custom-tailored to extract data from specific HTML components only. The data you need to get extracted depends on your business goals and objectives. There is no need to extract everything when you can specifically target just the data you need. This will also put less strain on your servers, reduce storage space requirements, and make data processing easier.
Setting up the server environment
To continually run your web scrapers, you need a server. The next step in this process is investing in server infrastructure or rent servers from an established company. Servers are a must-have as they allow you to run your data extraction scripts 24/7 and streamline data recording and storing.
Ensuring there is enough storage space
The deliverable of data extraction scripts is data. Large scale operations come with high storage capacity requirements. Extracting data from several websites translates into thousands of web pages. Since the process is continuous, you will end up with huge amounts of data. Ensuring there is enough storage space to sustain your scraping operation is very important.
Most data extraction services also come with data processing services because this is an absolute must-have. When you extract data from websites, it comes in raw form. You can’t benefit from raw data, so it has to be normalized, merged, and processed.
Which data do businesses target for extraction?
As we mentioned earlier, it is understandable that not all online data is the target of extraction. Your business goals, needs, and objectives should serve as main guidelines when deciding which data to pull.
When we are talking about data targets, you should know that there are no limits. You can extract product descriptions, prices, customer reviews and ratings, FAQ pages, how-to guides & more. You can also custom-tailor data extraction scripts to target new products and services.
Common data extraction challenges
Website data extraction doesn’t come without challenges. The most common ones are:
- Data gathering requires a lot of resources. If companies decide to start web scraping from e-commerce websites, they need to develop a particular infrastructure, write scraper code, and oversee the entire process. It requires a team of developers, system administrators, and other specialists.
- Maintaining data quality. Maintaining data quality across the board is of vital importance. At the same time, it becomes challenging in large-scale operations due to data amounts and different data types.
- Automation. Automating the data extraction process saves time and money. However, to completely automate your operation, you will have to bring in rotating proxies. We’ll address it more later on.
- Efficiently handling information variations in the target components. The same components on web pages can contain different types of variations. Developing a script able to pull everything and efficiently store it is somewhat challenging.
Scrapping e-commerce websites: the unique challenges
E-commerce websites are notorious for anti-scraping technologies. To ensure the best shopping experience for their consumers, they implement various anti-scraping solutions. In web scraping, one of the most important parts is to mimic organic user behavior. If you send too many requests in a short time interval or use the same IP address for scraping purposes, or you forget to handle HTTP cookies, there is a chance that servers are going to detect the bots and block your IP. If you want to know more about how to avoid being blocked by a target server, check out our other blog posts.
Also, every e-commerce scraping operation is a large-scale one. There are hundreds of product pages and thousands of customer questions, reviews, and answers. On top of that, e-commerce websites regularly update their structure, requiring you to update data extraction scripts constantly. Prices and inventory are also subject to constant change, and you need to keep the data extraction scripts going constantly.
Overcoming data scraping challenges
The challenges related directly to data extraction can be solved with a sophisticated data extraction script developed by experienced professionals. Maintaining an ongoing scraping operation is possible with out-of-the-box solutions such as real-time crawlers.
However, this still leaves you exposed to the risk of getting picked up and blocked by anti-scraping technologies. This calls for a completely different solution – proxies.
More precisely, rotating proxies. Rotating proxies will provide you with access to a large pool of IP addresses. Sending requests from IPs located in different geo regions will trick servers and prevent blocking. Additionally, you can use a proxy rotator. Instead of assigning different IPs manually, the proxy rotator will use the IPs in the proxy data center pool and assign them automatically.
To sum it up, you will need a data extraction script to extract data from a website. As you can see, building those scripts can be challenging due to the scope of operation, complex and changing website structures. Since the web scraping has to be done in real-time to get the most recent data, you will have to avoid getting blocked. This is why major scraping operations run on rotating proxies.
If you feel that everything is clear and you already want to start web scraping to achieve your goals for business, you can register and start using Oxylabs’ Real-Time Crawler right away. However, if you have some unanswered questions, feel free to discuss your case with our sales team by clicking here and booking a call.