So what is a data extraction and why would you automate it? Data extraction or scraping isn’t just searching for the information you need on the Internet. Modern challenges in web economics demand a bigger-scale approach. The amount of data you need to analyze grows exponentially due to a great number of factors. Only by gathering a huge amount of data simultaneously can you mine data and find necessary trends, which will provide new opportunities to your business.


Data extraction can be physical and logical. Logical extraction methods are based on datalog. There are two main types of logical extraction – full and incremental.

Full extraction

The full extraction method speaks for itself. It is probably the most primitive data extraction method. However, sometimes it is the only possible one. Full extraction means that you copy all the data bit by bit. This approach is indeed very useful while creating a new data warehouse. On the other hand, it is often not necessary to download all the available data. You will have to store it somewhere eventually.

Incremental extraction

If you are extracting data on daily basis for its comparison and analysis incremental extraction is better than full extraction. In this case, only the piece of data is extracted, where a so-called well-defined event took place. Simply it means you only take the data that has changed since your last extraction procedure. This may happen with 24, 48, or 72 hours of regularity. Physical methods that said are divided into online and offline methods.

Online extraction

In the case of online extraction, the data is extracted directly from the source system. During the online extraction, the process of data scraping can be connected to the source tables either to an intermediate data storage. Wherein the intermediate data storage system may not be physically different from the source system.

Offline extraction

Unlike the online method, in online extraction, the data isn’t taken from the source system itself but is stored outside it. You can consider flat-file or dump-file structures.


There are three main types of extraction tools used nowadays: batched tools, web-scraping tools, and cloud-based tools.

The batched tools

There are times when companies need to move data elsewhere, but face problems because such data is stored in obsolete forms or is outdated. In such cases, the best solution is to move the data in batches. This would mean that the sources may include one or more pieces of data and not be too complex. Batch processing can also be useful if you are moving data in a closed environment. Using this technique in non-working hours also effectively saves time and reduces overall used computing power.

Web-scraping tools

Web-scraping tools are software,  which is used to transfer open-source data from public and commercial websites into readable formats. This software includes bots such as crawlers to automate the extraction process.

Cloud-based tools

Cloud solutions ensure you will not just access the extracted data but also will be able to analyze it for sake of your business and money management. Usually, cloud-based tools are located within developers’ servers or on special cloud services for data maintenance.


Automated data extraction demands decent and specialized software. The separate pieces of the highly customized software in a single system. It is often called a web-scraper. Such scrapers consist of several key elements.

Data Fetching Software  

The first step in data extraction is data fetching. The software that is responsible for fetching uses HTML to call for data via the targeted websites’ codes. Fetchers imitate human activity on the Net. They never scroll any web pages as humans do though. A good web-scraper is capable to overcome all the targeted site’s defenses so that the website ‘decided’ it was a real human.

Spider Bots

Spider bots or web crawlers are Internet bots that automatically extract information from websites. These are key instruments for automated data extraction. Crawlers start with seeds – special URLs lists. As a crawler visits these URLs, it identifies all the web pages’ hyperlinks. Spider bots include these hyperlinks in the list of the URLs to visit, making data extraction a fast and automated process that needs no men to supervise.

Web Parsers

The aim of a parser is to structurize all the extracted data for further analysis and use. Parsers are crucial participants in data extraction processes. They compare newly extracted ‘fresh’ data with the older one, highlight all the changes. They are also responsible for reformatting the useful data from codes into readable formats and commonly used types of text files. They may store data within some hardware or in a cloud.


Sites’ Protection

Data extraction software development is not a voluntary process, the targeted websites are constantly improving protection against undesired data extraction. This is a real web arms race going on between commercial and other sites and web scraping software developers. As a rule, creators of data extraction systems do a great, yet costly job. Staying updated is a key to success for both: web scrapers developers and the programmers, who deal with websites’ antibot protection. Nowadays dynamic websites are being a really popular measure to overcome data extraction. This kind of web page is a great challenge. Dynamic sites make it impossible to access their data directly through HTML.

Sites’ Variousness

Different websites impose divergent approaches to their data extraction. In practice, it means that one cannot create a 100% efficient single system for data extraction that would work well with all websites. Software that can extract data from lots of websites at once will cost significantly more for the developers as well as for the clients.


Before building a data extraction system you will need to choose a proper tech stack. It is a vital issue, so here are some suggestions:

Programming languages

  • PHP
  • JavaScript
  • Python


  • Puppeteer
  • Playwright


  • Laravel
  • Symphony
  • React
  • Angular


  • MongoDB
  • Redis
  • PostgreSQL

Step 1. Define the data or the process you want to analyze

Data extraction tools may differ depending on the type of the data and kind of the source you want to extract the data from. Making your project’s aim clear is important for developers, who will embody your idea.

Step 2. Determine what questions should the extracted data answer

Not just the data extraction matters, but also the way how you are going to exploit the received information and what analysis methods ought to be used.

Step 3. Find a team

Having an adequate team is really important when you build a data extraction tool. It will affect the speed at which your project will be done as well as the expenses.

Step 4. Choose the tech stack

Once you know your project goals you can have your tech stack chosen. First of all, it will define your software possibilities, but also impact your team’s work speed and efficiency. 

Step 5. Troubleshooting and maintenance

After your product’s release you should not relax, but keep your team ready to update your software in response to any changes, cope with problems if they appear, and maintain all the system together with the data it has gathered.


Costs for the development of data extraction software vary dramatically. The final price is affected by many factors: the amount of data to work with, the kind of solution chosen, the number of data sources, integrations, and counter-protection tools inhibited. For a single site project, the tool may cost up to ten thousand dollars. If you need a larger project be ready to spend up to 200,000$. To save your budget you should consider outsourcing your project as well as defining your MVP. Hence you will gather extra resources to expand your system in the future.


SapientPro has extraordinary experience in data extraction development, we have effectively designed a lot of such software for commercial needs. Our team is searching for new approaches and solutions in the non-stop regime and our experience proves the efficiency of our tactics. We have successfully developed commercial software that extracts data on more than 25 million different goods at once with a 36 hours period. Our automated systems can effectively check changes in both text and media descriptions of the products or seek other types of data. The systems we made can simultaneously buy high-demand products within seconds for thousands of users without their direct involvement – automatically. 

As a software developing company, we can provide any services, including all the types of data extraction tools for any existing platforms. We will also provide you with our own cloud solutions to store all the data. Contact us and we will discuss your project together!