In 2024, knowing how to make 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 public data stored on servers across websites that can help businesses stay sharp in the competitive market.
For this reason, we’ll explain how data extraction works and the methods to do it, along with the pros and cons of each one. Then, we’ll cover the common challenges associated with web scraping.
Different ways for data extraction
There are several ways to extract public data from a webpage – building an in-house tool or using ready-to-use web scraping solutions. All options come with their own strengths; let's look at each to help you easily decide what suits your business needs best
Readily-available data
Readily-available data, oftentimes referred to as datasets, is exactly what it sounds like – it is a collection of information. The main thing with datasets is that you don’t have to worry about the process of gathering data. Instead, the provider delivers structured data that’s ready for analysis, so you can get to working with it right away. While it all sounds very convenient (given you don’t have to deal with possible blocks), datasets usually come at a higher price.
Now, what type of data can you get? Oxylabs, for example, currently offers six types of data, including company data, product review data, and others. Since you’re not in control of the data-gathering process, it’s important that the provider puts extra effort into tailoring the data to your needs.
3rd party tools
Another common approach to data is purchasing web scraping tools, usually APIs or proxies. Usually, APIs are entire web scraping infrastructures that ensure proxy rotation, data parsing, and other processes so that you can retrieve the data successfully and without blocks. Meanwhile, proxies are meant to be incorporated into your own web scraping infrastructure, meaning that you’ll have to take care of the maintenance.
There are other types of tools for scraping web data, as well. For example, Screaming Frog, which, paired with proxies, can successfully retrieve SEO data. Others use Google Sheets or Microsoft Excel, which makes for a convenient way to retrieve the data. Finally, there are headless browsers and web scraping extensions, so you’ve got plenty to choose from depending on your goals, budget, and scope.
Oxylabs Web Scraping API
Circling back to APIs, Oxylabs offers several scraping APIs (Application Programming Interfaces) to gather various types of data. Let’s take Oxylabs Web Scraper API as an example: it’s an all-in-one web scraping infrastructure that helps you gather publicly available data from the majority of websites: real estate, travel, entertainment, and others. With Web Scraper API, you don’t have to worry about dealing with CAPTCHA, potential IP blocks, or scraper maintenance, all of that is taken care of.
You can get a free trial for Web Scraper API by registering via our dashboard: you’ll get 7 days of 5K results to test it out.
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Official APIs
Some websites provide their own APIs for accessing their data. Typically, these APIs deliver structured, ready-to-use data so it’s a really convenient way. On the other hand, not all websites offer their own APIs and those that do may have limited options.
Web scraping services
If you have limited technical knowledge and do not want to deal with proxies or headless browsers, you can use a web scraping service for data acquisition. These services deal with the technical web scraping aspects so you don’t have to. To learn more, check out our blog post where we list the best no-code scraping tools.
In-house solution
The final option is building your own web scraper. For the most part, companies opt to build their own scrapers because it gives them more freedom. You don’t have to pay for features you don’t need, and vice versa, you get all the features you do need.
It also depends on the size of your company: if you require a small-scale scraper, building your own shouldn’t take up too much of your resources.
To develop an in-house website data extractor, you'll need a dedicated web scraping stack. Here's what it'll include:
Proxies. Many websites differentiate the content they display based on the IP address location. You might need another country's proxy, depending on where your servers and targets are.
A large proxy pool will also aid in avoiding IP blocks and CAPTCHAs.
Python, Node.js, or other programming language knowledge. To build your web scraper, you’ll need at least some level of programming skills. The most common language used in the web scraping space is Python.
Headless browsers. An increasing number of websites are using frontend frameworks like Vue.js or React.js. Such frameworks employ backend APIs to fetch data and render to draw the DOM (Document Object Model). Regular HTML clients wouldn't render the Javascript code; thus, without a headless browser, you'd get an empty page.
Also, websites often detect if HTTP clients are bots. In this case, headless browsers can aid in accessing the target HTML page.
The most popular APIs for headless browsers are Selenium Puppeteer Playwright
Extraction rules. It's a set of rules that you'll use to choose HTML elements and extract data. The simplest ways to select these components are XPath and CSS selectors
Websites are continuously updating their HTML code. As a result, extraction rules are the aspect on which developers spend most of their time.
Job scheduling. This allows you to schedule when you'd like to, let's say, monitor specific data. It also aids in error handling: it's essential to track HTML changes, target websites or your proxy server's downtime, and blocked requests.
Storage. Once you extract the data, you'll need to store it somewhere, like in an SQL database. Standard formats for saving gathered data are JSON, CSV, and XML.
Monitoring. Especially extracting data at scale might cause multiple issues. To avoid them, you need to make sure your proxies are always working properly. Log analysis, dashboards, and alerts can aid you in monitoring data.
All in all, here are the main stages of how to extract data from the web:
1. Decide the type of data you want to fetch and process.
2. Find where the data is displayed and build a scraping path.
3. Import and install the required prerequisites.
4. Write a data extraction script and implement it.
Imitating the behavior of a regular internet user is essential in order to avoid IP blocks. This is where proxies step in and make the entire process of any data harvesting task easier. We will come back to this later.
Which one to choose?
Whether it's better to build an in-house solution yourself or get a ready-to-use data extraction tool closely depends on the size of your business.
If you're an enterprise willing to collect data at a large scale, datasets or tools like Web Scraper API are the right choice: they'll save you time and provide real-time quality results. On top of that, you'll save your expenses on code maintenance and integration.
However, smaller businesses scraping the web only at times might fully benefit from developing their own in-house data extraction tool.
| Datasets | 3rd party tools | Web Scraper API | Official APIs | Web scraping services | In-house solution | |
|---|---|---|---|---|---|---|
| Pros | Ready for analysis, no blocks or need for technical knowledge | Not as expensive, more flexibility | No maintenance, CAPTCHAs or IP blocks | Convenience, structured data | Convenient, no need for technical knowledge | Flexibility, freedom |
| Cons | Expensive, may not be as flexible | May need maintenance, potential blocks | Requires some technical knowledge | Potential limitations | Potential limitations | Requires technical skills and resources |
Top extracted data types
It’s 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.
There can be loads of data targets that could be of interest to you, for example:
Product descriptions
Pricing data
Customer reviews and ratings
FAQ pages
Real estate listings
Flight data
Search engine results
…and more.
The important thing here is to make sure that you are scraping public data and not breaching any third-party rights before conducting any scraping activities.
Common data collection challenges
Extracting data doesn't come without challenges. The most common ones are:
Resources and knowledge. Data gathering requires a lot of resources and professional skills. If companies decide to start web scraping, 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.
Anti-scraping technologies. To ensure the best shopping experience for their consumers, e-commerce websites 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 forget to handle HTTP cookies, there is a chance that servers will detect the bots and block your IP.
Large-scale scraping operations. E-commerce websites regularly update their structure, requiring you to update your scripts constantly. Prices and inventory are also subject to constant change, and you need to keep the scripts always running.
Extracting data: how it works
If you are a not-that-tech-savvy person, understanding how to extract data can seem like a very complex and incomprehensible matter. However, 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 an automated process that is created with the intention to extract data using a bot or a web crawler. Other times, the concept of web scraping is confused with web crawling. For this reason, we have covered this issue in our other blog post about the main differences between web crawling and web scraping.
Now, we will discuss the whole process to fully understand how to extract web data.
What makes data extraction possible
Nowadays, the data we scrape is mostly represented in HTML, a text-based markup language. It defines the structure of the website's content via various components, including tags such as <p>, <table>, and <title>. Developers are able to come up with scripts that pull data from any manner of data structures.
Building data extraction scripts
Programmers skilled in programming languages like Python can develop web data extraction scripts, and 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 scripts can scrape data in an automated way. They send a request to a server, visit the chosen URL, go through every previously defined page, HTML tag, and components. Then, they pull data from them.
Developing various data crawling patterns
Scripts that are used to extract data can be custom-tailored to extract data from only specific HTML elements. 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. So, the next step in this process is investing in server infrastructure or renting servers from an established company. Servers are a must-have as they allow you to run your previously written 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.
Data processing
Acquired data comes in raw form and may be hard to comprehend for the human eye. Therefore, parsing and creating well-structured data is the next important part of any data-gathering process.
Benefits of web data collection
Big data is a new buzzword in the business world. It encompasses various processes done on data sets with a few goals – gaining meaningful insights, generating leads, identifying trends and patterns, and forecasting economic conditions. For example, web scraping real estate data helps to analyze essential influences in this industry. Similarly, alternative data can help fund managers reveal investment opportunities.
Another field where web scraping can be useful is the automotive industry. Businesses collect automotive industry data such 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.
Best practices of data scraping
The challenges related directly to web data collection can be solved with a sophisticated website data extraction script developed by experienced professionals. However, this still leaves you exposed to the risk of getting picked up and blocked by anti-scraping technologies. This calls for a game-changing solution – proxy servers. 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 manually assigning different IPs, the proxy rotator will use the IPs in the proxy data center pool and automatically assign them.
If you do not have the resources and team of experienced developers to start web scraping, it is time to consider a ready-to-use solution such as a Web Scraper API. It ensures high data delivery success rates from most websites, streamlines data management, and aggregates data for easier understanding.
Is it legal to extract data from websites?
While many businesses rely on big data, the demand has grown significantly. According to research by Statista, the big data market is increasing enormously every year and is forecasted to reach 103 billion U.S. dollars by 2027. It leads to more and more businesses adopting web scraping as one of the most common data collection methods. Such popularity evokes a widely discussed question of whether web scraping is legal.
Since this complex topic has no definite answer, one must ensure that any carried out web scraping does not breach any laws surrounding the said data. It is important to note that before engaging in any scraping activity, we firmly suggest seeking professional legal consultation regarding the specific situation.
Also, we strongly urge you to stay away from scraping any data that is non-public unless you have explicit permission from the target website. For clarity, nothing that was written in this article should be interpreted as advice for scraping any non-public data.
If you want to learn more about web scraping legality, read our article Is web scraping legal? where we have covered the topic in detail from the ethical and technical side.
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, complexity, and changing website structures. Since 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 your business requires an all-in-all solution that makes data collection effortless, you can contact us at hello@oxylabs.io
People also ask
Is there a way to deal with advanced anti-bot systems?
You can use tools like Web Unblocker, which is an AI-powered proxy solution capable of bypassing sophisticated anti-bot systems, dealing with CAPTCHA, and imitating an organic user.
How do I extract data from a website into Excel?
There are several ways to extract data, so it’s transferred to Excel. We have a couple of tutorials available:
How do I extract hidden data from a website?
The most common way to scrape dynamic data is to use a headless browser to force hidden data rendering in the HTML. Also, make sure you’re meeting the local laws and regulations.
How do I extract data from a website into a Google sheet?
To extract data from a website and transfer it to a Google sheet, follow this tutorial:
About the author
Iveta Vistorskyte
Lead Content Manager
Iveta Vistorskyte is a Lead Content Manager at Oxylabs. Growing up as a writer and a challenge seeker, she decided to welcome herself to the tech-side, and instantly became interested in this field. When she is not at work, you'll probably find her just chillin' while listening to her favorite music or playing board games with friends.
All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.
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