If you think that data extraction or web scraping is just for businesses, tech experts or those who are exclusively invested in the data scene profession, you’re missing out.
Why data matters
In the digital age, data is the unsung hero, touching lives and making an impact that’s often unnoticed. Today, data shapes how we work, play, and connect. It’s the driving force behind personalized Netflix recommendations, weather forecasts, and that underrated song that you came across on YouTube.
As our experiences weave themselves into the vastness of the internet, we leave a trail of our preferences. Technically, its referred to as the digital footprint. You create an account of what you do online including the sites you visit, comments you leave, or the links you click.
How do digital footprints play a role? Here are a few stats to put that into perspective:
- An average internet user spends around 6 hours and 58 minutes online daily.
- Approximately 100,000 Google searches take place every second.
- Regular internet users generate a staggering 70% of the world’s data.
In this regard, the significance of data is paramount. Whether you’re a business seeking to understand consumer preferences, a researcher delving into the depths of online content, or just a curious individual wanting to uncover insights on the web, data acts as your compass to unlock a wealth of knowledge you care about.
Data extraction and no-code scraping
When data guides your decisions, there’s little chance you’ll lag. But, when efficiency and productivity are key, having to copy-paste relevant datasets across multiple websites repeatedly onto a spreadsheet is a nightmare. An efficient alternative? Automating the entire process with web scraping. Simply put, web scraping is the process of extracting relevant information in the form of data points from the websites of your choice.
Easier said than done, web scraping is a complex process. If we think of the resources and the efforts it takes, scraping the web can be daunting for many. But that should not stop you from accessing the data you need.
Experts estimate that 70% of new business applications will use no-code technologies by 2025! Similarly, analysts expect the average market size of the no-code/low-code market to grow at a CAGR of 31.9% by 2027. The rise of no-code scraping tools has made it easier for those interested in acquiring data to do so on their own, without having to worry about the technicalities.
No-code data extraction tools play a vital role today in ensuring data accessibility for all. By handling the technicalities on behalf of the users, web scraping has become simple enough to involve a point-and-click interface, without compromising on the quality of data extracted. This means web scraping is no longer limited to tech-savvy individuals. You can get started with just a few clicks, allowing the possibility to access a vast amount of information quickly and easily.
Myths on usability of no-code scrapers
Web scraping has become a matter of interest for many. So if you’re new to the realm of data extraction, and have found the possibilities of simplifying your data collection process to be intriguing, you’re on the right track. But as alluring as the idea of no-code web scraping sounds, it comes with a few stereotypes.
If you’re a beginner, you must have thought about these at least once. We’ll bust the myths for you:
No-code scraping is prone to errors
No-code platforms are equipped with validation mechanisms and error-checking features. While the precision of the data collected depends on proper configuration, these tools are designed to minimize errors and ensure reliable data extraction.
No-code scraping is expensive
No-code tools provide a cost-effective solution to extract required data within a short time. It also eliminates the need for extensive development time and resources. Further, many platforms offer tiered pricing plans to accommodate different user needs and budgets – you can start with a free plan and upgrade your package as per your requirements.
No-code tools lack customization
Most no-code scraping tools offer opportunities for users to customize through configurable settings and parameters. Users can tailor the extraction process to their unique needs without delving into intricate codes.
No-code scraping is not scalable
No-code scraping solutions can seamlessly handle small-scale extraction tasks. While it’s true that they have limitations compared to custom-coded solutions, many tools are designed to efficiently manage basic to intermediate scraping requests without compromising performance.
Key considerations when choosing web scraping tools
The tools you employ determine the outcome you’ll have. It’s tempting to trust the claims and adopt low-cost tools, but it will compromise the long-term impact.
Ease of use
Data extraction can be a simple point-and-click process if the interface is easy to navigate. A cluttered tool impacts productivity. Tools with a clean interface make it easier to set up and manage scraping tasks, especially for users with varying levels of technical expertise. Any tool that aims to simplify the extraction process for you should not assume your expertise. A guided text of the next step and what to expect goes a long way in ensuring a seamless user experience.
Scalability
Generally, data extraction requirements grow over time. When choosing a tool, you should assess your scraping requirements – for now and in the future. Consider if you’re using the tool for a one-time extraction for a research project, or if data collection will be a recurring process. In addition, ensure that the tool can handle the volume and complexity of data extraction tasks you anticipate, both in terms of the number of websites and the amount of data you wish to collect.
Flexibility and customization
Content on a website can be structured or unstructured. Structured websites have an organized and consistent arrangement of data on a website. Unstructured websites, on the other hand, have irregular and varied structures, with poorly formatted HTML markup, the inclusion of dynamic content loading techniques using JavaScript or AJAX, or insufficient metadata descriptions. These issues make it difficult for the scrapers to identify and extract relevant data accurately and at scale. Consider if your targeted websites are easy to scrape. It’s best to aim for tools equipped to handle varying structures to extract relevant data at scale.
Error handling mechanisms
An inefficient tool brings in inaccurate data. To combat errors in the data collection process, it is essential to opt for tools with built-in error handling mechanisms to manage issues like connection failures, website changes, or unexpected interruptions. This ensures a more reliable and resilient scraping process, allowing you to pick up right where you left off.
Cost and licensing
Extraction requirements evolve. It is crucial to make sure that the tools we employ serve our long-term objective. Before settling on a tool, you should evaluate the cost structure of the web scraping tool alongside factors like subscription fees, data transfer costs, and any additional charges for advanced features. It is wise to opt for a tool that best aligns with your budget and usage requirements.
Updates and maintenance
Frequent updates are a must for any technical tool. It is essential to track the tool’s update frequency and maintenance policy. Extraction tools with regular updates indicate that the tool is actively maintained, allowing you to efficiently adapt to website changes and evolving technologies.
End notes
Data plays a crucial role in staying ahead in the game regardless of the game you’re playing. To make things easier, data accessibility has largely been democratized with the development of no-code or low-code tools. Today, when it comes to data, don’t just test the waters; just dive in!
Whether you’re a newbie or a native to data extraction, tools like Pline is your gateway to quality data ready for instant analysis – all without the hassle of coding.
