How to Design a Web Scraping Solution: A Step-by-Step Guide
For many people, especially those without technical skills, developing a web scraping solution architecture and estimating the necessary resources can be a complex process.
Often, this is their first web scraping project, so they have little experience and reference materials to rely on when assessing the feasibility of a data collection project.
In this overview article, we will provide you with a general overview of our solution architecture development process so that you can use it and apply it to your own projects.
Step 1: Defining Data Requirements
The goal of this stage is to minimize the number of unknown variables and reduce assumptions as much as possible, so that the development team can design an optimal solution for business tasks.
This is also important for those developing a web scraping infrastructure for their projects. Accurately defining project requirements will allow your development team to ensure that your web scraping project precisely aligns with your business goals.
Here, you need to establish:
- User needs - what business or personal goal do you want to achieve? How will web data help you achieve this goal?
- Your data requirements - exactly what data do you need to achieve your business or personal goal? From which websites and how often? Etc.
It is important that your data requirements precisely match your core goals and needs. Quality data can give your business a competitive edge in the market, but it is crucial to have the right data.
Extracting data from the internet is a fairly simple task, but extracting the right data with the required frequency and quality for business processes is a complex challenge.
However, when evaluating a web scraping project, it is always necessary to determine:
- What data is needed, i.e., exactly what data do you want to obtain during the scraping process.
- From which websites do you want to obtain this data?
- How often do you want to receive this data? Daily, weekly, monthly, one-time, etc.?
- How do you plan to use this data?
- How do you plan to verify the accuracy of the extracted data, i.e., its precise match with the data on the target websites?
- How do you plan to interact with the solution, i.e., receive data at a specified interval or control the entire web scraping infrastructure and corresponding source code?
Step 2: Conducting Legal Due Diligence
The second stage is to check for any legal obstacles to data extraction.
Given that awareness of internet security and data privacy has increased in recent years, compliance of a web scraping project with legal requirements is mandatory. Otherwise, you may put yourself or your company in a difficult position.
In general, the project should be evaluated based on the following criteria:
- Personal data - do you need to extract personal data? If so, where do the individuals whose data will be extracted reside? Do you need to comply with local regulations? For example, GDPR.
- Copyrighted data - is the data subject to copyright? If so, are there any copyright exceptions you can utilize?
- Database rights - does the website from which data is extracted hold database rights?
- Data behind login - do you need to scrape behind a login to extract data? What do the website's terms and conditions say about web scraping?
Step 3: Assessing Technical Feasibility
If the project has successfully passed legal due diligence, the next step is to assess the technical feasibility of successfully implementing the project.
This is a very important step in our solution architecture development process, which unfortunately is often overlooked by many independent developers working on their own projects or their companies' projects.
Developers and company managers often jump straight into working on the solution. This may work for simple projects, but in more complex projects, technical challenges may arise.
During the technical analysis phase, our solution architect will study the website and conduct a series of small tests to assess the technical feasibility of creating a solution that meets the client's requirements (crawl speed, coverage, and budget constraints).
These tests are primarily designed to assess the complexity of data extraction, any rate or frequency limitations, ease of data discovery, the need for additional technologies, etc.
Our solution architect obtains the information needed to determine the technical feasibility of the project and subsequently develop the optimal solution architecture.
Step 4: Solution Architecture and Resource Estimation
The final stage in the solution architecture creation process is to develop the architecture and estimate the technical and human resources required to implement the project.
In most cases, the solution must be approached in stages to find a balance between timeline, budget, and technical feasibility. We propose an optimal first step for implementing your project while keeping the main goal in mind.
The web scraping infrastructure is built using the following building blocks:
- Crawler architecture - spider architecture for data discovery and extraction.
- Spider deployment
- Proxy server management
- Headless browser requirements
- Data quality assurance
- Maintenance requirements
- Data post-processing
- Any specialized technologies that may be required.
After developing the solution architecture and estimating resources, we provide all necessary information to the client and estimate the project cost. We also create a technical specification that reflects all requirements and the proposed solution.
If you need to start or expand a web scraping project, our scraping specialists are ready to provide a free consultation, during which we will evaluate and design a data extraction solution that meets your data requirements and regulatory obligations.