Web scraping is one of the most common corporate practices. It’s a pillar of data science – you equip a bot with a couple of proxies and let it loose on the world wide web so that it can collect as much data as possible. It’s one of the key business techniques in today’s data-driven world.
Now, while web scraping has experienced a renaissance with the addition of proxies that allowed it to dig deep into databases, its second renaissance comes in the form of AI.
Below, we will talk about web scraping in general, define what issues plague the practice, and explore how AI can make it all better.
Current State of Web Scraping
In its current state, web scraping is an integral business practice and the best method for accumulating as much data as possible. It is technically setting up an algorithm or software to scour the internet for relevant data.
In most cases, it is made better through proxies. By adding proxies to web scraping algorithms, you can actively pass through many restrictions and firewalls put in place by websites to protect their data.
Autodetection algorithms and bans can’t stop your bot, as they switch their IP address and dig deeper to collect more data.
The software that powers web scraping bots has advanced by a considerable margin and is getting more and more automated with every incarnation.
Automation for the Future
Automation is a thing of the future today. A lot of our lives are automated, whether we know it or not. When it comes to corporate applications, automation is the end goal, meaning that any technology that can automate any business task is probably currently in development.
A good solution to quite a lot of these automation conundrums is artificial intelligence. While we’re not at HAL9000 levels yet, AI can do many things at a far faster rate than humans. Not only can it control and steer bots, but you can also use it to process everything from transactions to data collection.
Issues With Scraping Today
Web scraping, in its current incarnation, suffers from more than a couple of issues. Not to say that the process isn’t working – it’s just that a lot of its aspects can be improved.
Modern web scraping solutions are relatively slow and need to rummage through a huge amount of data to index all of it.
Perhaps the biggest pitfall of modern web scraping is that the data collected isn’t that high in quality. It’s very hard to steer the software in the right direction, and while you can point it towards what type of data you’re looking for, you can’t make it individually pick out the cream of the crop.
All the data collected from web scraping is raw data, which in turn must be processed before its subject to analysis.
Introducing AI Web Scraping
AI web scraping is like web scraping 2.0. It’s better in every way – the only thing that may be considered a downside is that currently, AI web scraping services and solutions are a bit on the higher end price-wise.
AI web scraping solves most of the issues that modern regular web scraping suffers from.
Introducing artificial intelligence technology to web scraping allows the software to take an entirely different approach to data collection, which yields a faster, higher-quality result.
Benefits of AI-Powered Scraping
AI-powered web scraping is the future of web scraping. Web scraping technology is advancing rapidly, and so is AI. The merger of these two technologies will revolutionize webs cramping from the ground up, allowing AI-powered web scraping bots to:
- Select the type of data they produce;
- Procure a higher quality of data;
- Dig deeper into databases;
- Solving puzzles and captchas;
- Far higher scraping success rate;
- Minimize the need for data refinement.
These are just some of the most notable benefits of AI-powered web scraping – as AI web scraping continues to evolve, so will its applications.
Web scraping is already an integral part of modern-day corporate needs. As we’re moving towards a more and more data-driven world, data has become one of the most valuable assets a business could have, and a revolutionary technology such as AI web scraping could change how the data is procured.
It increases the quality of the data that’s collected, but it also minimizes the amount of refinement necessary and speeds up the entire process considerably.