Exploring How Web Scraping Goes Beyond Simple Data Extraction
Exploring How Web Scraping Goes Beyond Simple Data Extraction
The conversation on big data globally continues to expand. The data analytics industry was valued at $49 billion in 2022 and is expected to maintain a compound annual growth rate of 26.7% till 2030.
However, one of the aspects of data analytics that has often been overlooked or underutilized is web scraping. In this article, we explore what web scraping is and how companies can benefit from this innovation. We also outline the steps for an effective web scraping exercise.
What is Web Scraping?
Web scraping is a method of obtaining data from websites. Depending on the project, it is sometimes part of the data analysis process. Data analytics services and professionals typically extract large volumes of data, including text, audio, image, or video. This information is then stored, cleaned, and used to discover insights for decision-making.
The Rise of Web Scraping and Big Data Analytics
Data is the building block of most thriving 21st-century organizations. In today’s cut-throat business space, companies that can use the vast amounts of data generated daily will maintain an edge over their competitors.
Data analytics services have become increasingly popular because they can source, organize, and analyze data and guide company executives in decision-making. However, one of the challenges of big data analytics is finding reliable data sources to build a robust sample size for analysis.
To curb this limitation, many data professionals rely on web scraping to gather the information they need from reputable websites. With web scraping, analysts can curate large datasets that are useful in understanding specific business problems.
Web Scraping vs. Screen Scraping
Two terms that are often used interchangeably among data analysts are web scraping and screen scraping. While these practices share some similarities, they also have a few differences, especially in the type of data they collect and the methods involved.
As explained earlier, web scraping refers to the process of extracting data from websites. Usually, this will involve crawling the websites with a scraping bot, retrieving relevant datasets, and presenting the data in a machine-readable format such as CSV, JSON, or XML for analysis.
Screen scraping, on the other hand, involves retrieving data from screens. Unlike web scraping, which is primarily restricted to websites, screen scraping can collect information from software applications, PDF files, and other types of documents displayed on a device’s screen. Data from screens can be accessed manually or automatically. However, this option is severely limited for obtaining big data.
Screen scraping differs from web scraping in its preferred data format. Data gathered from screens is usually unstructured and sometimes not machine-readable. For example, when the data type is a screenshot from a document or an image, the data analyst must use an Optical Character Recognition (OCR) program to parse the text and convert it into a readable format.
The table below clearly highlights the significant differences between web scraping and screen scraping.
Web Scraping |
Screen Scraping |
---|---|
Can retrieve structured and unstructured data | Gathers unstructured data from desktop or mobile screens |
Standard data formats include JSON, CSV, or XML | Often requires OCR to convert images or screenshots into machine-readable formats |
Requires scraping bots and web crawlers | Can be done manually or automatically |
Suitable for big data | Better for small and mid-sized datasets |
Extracts data from web pages | Used to obtain data from a broader range of sources like applications, images, and PDFs. |
Web Scraping vs. Web Crawling
Another term that is hard to distinguish from web scraping is web crawling. Many data analysts sometimes struggle to differentiate between both expressions because they are equally crucial in data extraction.
The goal of web scraping is to extract data from websites. However, the challenge is that you might not know the web pages that have the information you require. This is where web crawling becomes valuable.
Web crawling is the process of finding links on the internet. As the name implies, web crawlers scan through pages, index them, and organize them so that web scrapers can get the information required for analysis. In other words, data extraction from web pages demands crawling and scraping.
If you still find both terms confusing, here is a table outlining the difference between web scraping and web crawling.
Web Scraping |
Web Crawling |
---|---|
Outputs a wide range of data fields | Outputs links to websites |
Requires a scraping bot or web scraper | Uses a web crawler |
Aims to extract data from URLs | Seeks to curate and index a list of URLs |
Output can be used for decision-making in various industries and sectors | Output requires scraping to be valuable for data analysis |
Where is Web Scraping Used?
Web scraping has seen a massive increase in its use cases across many industries, including e-commerce, real estate, healthcare, and consulting. For example, Although most businesses have recognized the need for data-driven decision-making, many have yet to grasp the role web scraping can play in finding trustworthy data sources.
Here are some of the common ways web scraping is defining the trajectory of businesses in pivotal industries.
Web Scraping in E-Commerce
The e-commerce industry is highly competitive. Customers can access an endless list of businesses offering the same product; hence, retaining old users and attracting new buyers can be challenging.
Many businesses have continued to thrive by leveraging data from web scraping. Compared to other sectors, price competition is arguably the highest in e-commerce. Web scraping is helpful in gathering prices of similar products on competitor sites to determine sales strategy. A perfect example is a Morrocan car sales company that used web scraping to build a robust database of second-hand car sales from the top C2C e-commerce platforms.
While it would ordinarily be difficult to locate extensive documentation of price listings, web scraping readily provides this information readily. E-commerce companies use web scraping to collect data, which is used to make decisions, predict trends, adjust prices, and determine sales campaigns.
Web Scraping in Finance
Financial services is a very research-intensive industry. Organizations in this space rely on data from web scraping to stay up-to-date with the continuously changing market landscape. It has already been established that web scraping provides access to an extensive database that would otherwise be inaccessible.
Finance companies use web scraping to gather this treasure trove of information and filter it to discover trends and make forecasts. Often, this technology is used by data analysis companies as a precursor to performing predictive analysis. Working with data obtained from websites, financial service businesses can navigate the increasing market complexities and conduct thorough due diligence.
Web Scraping in Healthcare
Healthcare service providers benefit from web scraping in several ways. Data analytics companies with healthcare organizations sometimes use web scraping to obtain research data or make critical decisions. For example, pharmaceutical companies can apply web scraping to determine a suitable price point for their new drug.
Hospitals that prioritize data and use scraping programs to gather enough information will likely offer better patient care and be current with best practice standards.
Web Scraping in Advertisement and Marketing
Marketing and advertising require an in-depth understanding of customer behavior and preferences. To create effective advertisements and marketing campaigns, many companies rely on data scraped from websites, including competitor pages.
Web scraping has facilitated a rise in data-driven marketing discoveries. Rather than taking shots in the dark, regular businesses and advertising agencies can develop personalized strategies for specific demographics and contexts.
Benefits of Web Scraping
Businesses can gain a lot by incorporating web scraping services. Adding web scraping to your data analytics process potentially increases the information at your fingertips and boosts your chances of accurate analysis.
Here are some benefits of including web scraping in your data-driven decision-making workflow.
Affordability
Data gathering can be costly. Companies that operate a manual data collection system often have to conduct surveys or hire many experts to obtain the data they need for effective decision-making. Web scraping eliminates this reliance on manual labor and makes it cheaper to acquire information. By engaging the services of a web scraping company, businesses can get top-notch quality at a fraction of the price.
Access to Detailed Datasets
It’s no news that at least 90% of global data has been produced post-2018. As the number of internet users continues to increase, people are generating data about their preferences and interests at an alarming rate.
Most of this information is available via websites and APIs and can be obtained via web scraping. Web scraping companies give you access to reliable and comprehensive datasets. Organizations are more likely to find all the parameters they need to conduct their research via web scraping than any other means of data collection.
Scalability
As companies continue to grow and expand their market reach, they must incorporate methods to handle this increased demand. Web scraping is an excellent data collection method because of its scalability.
Depending on the specific business problem, you can collect more data or have access to data from a wider range of sources.
Saves Time
In business, they say time is money. If that’s the case, then web scraping is an invaluable asset because it can achieve much in relatively little time. Companies that have run a manual data analysis exercise know how cumbersome and time-consuming it can be.
These disadvantages and the fact that manual processes are prone to human error make web scraping a better option for any business. Web scraping is an automated process. Hence, data analytics companies that use this technology always deliver quickly.
By implementing web scraping, you can free up time for other critical business challenges and increase the speed of your decision-making at all levels.
Produces Reliable Data
The problem with manual data collection methods such as surveys is that you can still obtain inaccurate data despite the amounts spent. User responses can be skewed, and your analytics team can make critical mistakes during the data collection process that will affect the quality of insights you derive from the available data.
Web scraping services reduce errors at the data-gathering stage. They allow organizations to obtain reliable data and store it in a readable format. Furthermore, because web scraping gives access to large amounts of data, businesses can be more confident in the results of their data analysis.
According to the law of large numbers, the larger a randomly distributed dataset, the more likely it is to be genuinely representative of the population. Web scraping allows companies to obtain enough information to accurately sample the population or event they wish to study.
How to Conduct an Effective Web Scraping Exercise
Although web scraping has countless benefits, it must be done appropriately to produce exceptional results. Top-rated web scraping companies like Infomineo have a four-step process to ensure that their web scraping yields accurate datasets.
Identify Your Web Scraping Goals
Before you get started, it is important to decide the nature of the data you want to scrape. This information will guide your approach and help you streamline which websites to scrape from. Companies have different reasons for gathering data.
For example, while one business may need customer behavioral data, another may need pricing information for competitor products. Depending on your reasons for collecting data, you can decide how to proceed with the rest of the web scraping exercise.
Evaluate Your Data Sources
Once your goals are clearly outlined and you’ve determined the websites you want to scrape for the data you need, you must evaluate these sources across various indices such as privacy, reliability, and structure.
Check each web page’s privacy policies and sitemap to see if they allow third parties to scrape their data. Also, be sure that you are collecting data from a trustworthy source. It is also important to confirm whether the data you need is in a format that can be scraped.
Estimate the Volume and Complexity of the Data
The amount of data your company needs will depend on the purpose of the data collection exercise. While some problems can be addressed with small or medium-sized datasets, others require enormous data.
Another factor to consider is the complexity of the datasets – the nature of parameters needed and their type. Extremely complex datasets typically take longer to clean and prepare for analysis.
Select Your Tools and Build Your Scraper
Next, you need to select the tools that will enable you to scrape data effectively. You can hire programmers to create a custom solution from scratch or rely on an existing scraping bot. Companies that use web scraping services can save themselves the time spent exploring various tools and focus on core business tasks. They can also be assured that the web scraping exercise will follow best practice standards.
Consider Data Storage
Storage is the final piece of a data extraction process. Once data has been scraped, it must be preserved in a database or file for further action. Web scraping services use popular databases such as MongoDB or MySQL or save the results of the data collection exercise in CSV, JSON, or XML format.
FAQs (Frequently Asked Questions)
Is web scraping legal?
While web scraping is not illegal, it must be carried out cautiously to avoid breaking copyright laws. Since there are currently no concrete laws regulating web scraping, it is essential to determine the position of the website on scraping before proceeding.
Also, if you are handling the web scraping exercise yourself, you can consult with a legal expert to ensure that you remain within the boundaries of the law.
Can I scrape data from behind a login page?
Yes, you can, provided you have valid login details.
Why do I need a web scraping service?
Web scraping services are useful for companies that cannot handle the complexities of a large data project or the resources to build a web scraping service from scratch.
How long does web scraping take?
It depends on how many websites a scraper has to parse and the sizes of each website. Companies that intend to build an in-house infrastructure to perform a continuous, large-scale web scraping project can take months to complete the exercise. However, web scraping services such as Infomineo can complete similar projects relatively quickly.
Conclusion
Web scraping has evolved beyond a means of data extraction to become a pillar of modern-day big-data analysis. Companies now depend on the information obtained via web scraping to identify trends, forecast business outcomes, understand their customers, and improve their decision-making.
However, since most businesses do not have the in-house personnel or resources to build a robust data analysis architecture that includes web scraping, they now opt for data analysis companies that provide this feature.
The consensus is that data will be the defining factor for the coming years across various industries. By incorporating all means to collect data and stay in touch with current business best practices, companies can retain their customers, increase their revenues, and create lasting impact.